Network Working Group                                         D. Awduche
Request for Comments: 3272                                Movaz Networks
Category: Informational                                          A. Chiu
                                                         Celion Networks
                                                              A. Elwalid
                                                              I. Widjaja
                                                     Lucent Technologies
                                                                 X. Xiao
                                                        Redback Networks
                                                                May 2002

Overview and Principles of Internet Traffic Engineering

Status of this Memo

   This memo provides information for the Internet community.  It does
   not specify an Internet standard of any kind.  Distribution of this
   memo is unlimited.

Copyright Notice

Abstract

   This memo describes the principles of Traffic Engineering (TE) in the
   Internet.  The document is intended to promote better understanding
   of the issues surrounding traffic engineering in IP networks, and to
   provide a common basis for the development of traffic engineering
   capabilities for the Internet.  The principles, architectures, and
   methodologies for performance evaluation and performance optimization
   of operational IP networks are discussed throughout this document.

   1.0 Introduction...................................................3
      1.1 What is Internet Traffic Engineering?.......................4
      1.2 Scope.......................................................7
      1.3 Terminology.................................................8
   2.0 Background....................................................11
      2.1 Context of Internet Traffic Engineering....................12
      2.2 Network Context............................................13
      2.3 Problem Context............................................14
         2.3.1 Congestion and its Ramifications......................16
      2.4 Solution Context...........................................16
         2.4.1 Combating the Congestion Problem......................18
      2.5 Implementation and Operational Context.....................21

   3.0 Traffic Engineering Process Model.............................21
      3.1 Components of the Traffic Engineering Process Model........23
      3.2 Measurement................................................23
      3.3 Modeling, Analysis, and Simulation.........................24
      3.4 Optimization...............................................25
   4.0 Historical Review and Recent Developments.....................26
      4.1 Traffic Engineering in Classical Telephone Networks........26
      4.2 Evolution of Traffic Engineering in the Internet...........28
         4.2.1 Adaptive Routing in ARPANET...........................28
         4.2.2 Dynamic Routing in the Internet.......................29
         4.2.3 ToS Routing...........................................30
         4.2.4 Equal Cost Multi-Path.................................30
         4.2.5 Nimrod................................................31
      4.3 Overlay Model..............................................31
      4.4 Constraint-Based Routing...................................32
      4.5 Overview of Other IETF Projects Related to Traffic
          Engineering................................................32
         4.5.1 Integrated Services...................................32
         4.5.2 RSVP..................................................33
         4.5.3 Differentiated Services...............................34
         4.5.4 MPLS..................................................35
         4.5.5 IP Performance Metrics................................36
         4.5.6 Flow Measurement......................................37
         4.5.7 Endpoint Congestion Management........................37
      4.6 Overview of ITU Activities Related to Traffic
          Engineering................................................38
      4.7 Content Distribution.......................................39
   5.0 Taxonomy of Traffic Engineering Systems.......................40
      5.1 Time-Dependent Versus State-Dependent......................40
      5.2 Offline Versus Online......................................41
      5.3 Centralized Versus Distributed.............................42
      5.4 Local Versus Global........................................42
      5.5 Prescriptive Versus Descriptive............................42
      5.6 Open-Loop Versus Closed-Loop...............................43
      5.7 Tactical vs Strategic......................................43
   6.0 Recommendations for Internet Traffic Engineering..............43
      6.1 Generic Non-functional Recommendations.....................44
      6.2 Routing Recommendations....................................46
      6.3 Traffic Mapping Recommendations............................48
      6.4 Measurement Recommendations................................49
      6.5 Network Survivability......................................50
         6.5.1 Survivability in MPLS Based Networks..................52
         6.5.2 Protection Option.....................................53
      6.6 Traffic Engineering in Diffserv Environments...............54
      6.7 Network Controllability....................................56
   7.0 Inter-Domain Considerations...................................57
   8.0 Overview of Contemporary TE Practices in Operational
       IP Networks...................................................59

   9.0 Conclusion....................................................63
   10.0 Security Considerations......................................63
   11.0 Acknowledgments..............................................63
   12.0 References...................................................64
   13.0 Authors' Addresses...........................................70
   14.0 Full Copyright Statement.....................................71

1.0 Introduction

   This memo describes the principles of Internet traffic engineering.
   The objective of the document is to articulate the general issues and
   principles for Internet traffic engineering; and where appropriate to
   provide recommendations, guidelines, and options for the development
   of online and offline Internet traffic engineering capabilities and
   support systems.

   This document can aid service providers in devising and implementing
   traffic engineering solutions for their networks.  Networking
   hardware and software vendors will also find this document helpful in
   the development of mechanisms and support systems for the Internet
   environment that support the traffic engineering function.

   This document provides a terminology for describing and understanding
   common Internet traffic engineering concepts.  This document also
   provides a taxonomy of known traffic engineering styles.  In this
   context, a traffic engineering style abstracts important aspects from
   a traffic engineering methodology.  Traffic engineering styles can be
   viewed in different ways depending upon the specific context in which
   they are used and the specific purpose which they serve.  The
   combination of styles and views results in a natural taxonomy of
   traffic engineering systems.

   Even though Internet traffic engineering is most effective when
   applied end-to-end, the initial focus of this document document is
   intra-domain traffic engineering (that is, traffic engineering within
   a given autonomous system).  However, because a preponderance of
   Internet traffic tends to be inter-domain (originating in one
   autonomous system and terminating in another), this document provides
   an overview of aspects pertaining to inter-domain traffic
   engineering.

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
   document are to be interpreted as described in RFC 2119.

1.1. What is Internet Traffic Engineering?

   Internet traffic engineering is defined as that aspect of Internet
   network engineering dealing with the issue of performance evaluation
   and performance optimization of operational IP networks.  Traffic
   Engineering encompasses the application of technology and scientific
   principles to the measurement, characterization, modeling, and
   control of Internet traffic [RFC-2702, AWD2].

   Enhancing the performance of an operational network, at both the
   traffic and resource levels, are major objectives of Internet traffic
   engineering.  This is accomplished by addressing traffic oriented
   performance requirements, while utilizing network resources
   economically and reliably.  Traffic oriented performance measures
   include delay, delay variation, packet loss, and throughput.

   An important objective of Internet traffic engineering is to
   facilitate reliable network operations [RFC-2702].  Reliable network
   operations can be facilitated by providing mechanisms that enhance
   network integrity and by embracing policies emphasizing network
   survivability.  This results in a minimization of the vulnerability
   of the network to service outages arising from errors, faults, and
   failures occurring within the infrastructure.

   The Internet exists in order to transfer information from source
   nodes to destination nodes.  Accordingly, one of the most significant
   functions performed by the Internet is the routing of traffic from
   ingress nodes to egress nodes.  Therefore, one of the most
   distinctive functions performed by Internet traffic engineering is
   the control and optimization of the routing function, to steer
   traffic through the network in the most effective way.

   Ultimately, it is the performance of the network as seen by end users
   of network services that is truly paramount.  This crucial point
   should be considered throughout the development of traffic
   engineering mechanisms and policies.  The characteristics visible to
   end users are the emergent properties of the network, which are the
   characteristics of the network when viewed as a whole.  A central
   goal of the service provider, therefore, is to enhance the emergent
   properties of the network while taking economic considerations into
   account.

   The importance of the above observation regarding the emergent
   properties of networks is that special care must be taken when
   choosing network performance measures to optimize.  Optimizing the
   wrong measures may achieve certain local objectives, but may have

   disastrous consequences on the emergent properties of the network and
   thereby on the quality of service perceived by end-users of network
   services.

   A subtle, but practical advantage of the systematic application of
   traffic engineering concepts to operational networks is that it helps
   to identify and structure goals and priorities in terms of enhancing
   the quality of service delivered to end-users of network services.
   The application of traffic engineering concepts also aids in the
   measurement and analysis of the achievement of these goals.

   The optimization aspects of traffic engineering can be achieved
   through capacity management and traffic management.  As used in this
   document, capacity management includes capacity planning, routing
   control, and resource management.  Network resources of particular
   interest include link bandwidth, buffer space, and computational
   resources.  Likewise, as used in this document, traffic management
   includes (1) nodal traffic control functions such as traffic
   conditioning, queue management, scheduling, and (2) other functions
   that regulate traffic flow through the network or that arbitrate
   access to network resources between different packets or between
   different traffic streams.

   The optimization objectives of Internet traffic engineering should be
   viewed as a continual and iterative process of network performance
   improvement and not simply as a one time goal.  Traffic engineering
   also demands continual development of new technologies and new
   methodologies for network performance enhancement.

   The optimization objectives of Internet traffic engineering may
   change over time as new requirements are imposed, as new technologies
   emerge, or as new insights are brought to bear on the underlying
   problems.  Moreover, different networks may have different
   optimization objectives, depending upon their business models,
   capabilities, and operating constraints.  The optimization aspects of
   traffic engineering are ultimately concerned with network control
   regardless of the specific optimization goals in any particular
   environment.

   Thus, the optimization aspects of traffic engineering can be viewed
   from a control perspective.  The aspect of control within the
   Internet traffic engineering arena can be pro-active and/or reactive.
   In the pro-active case, the traffic engineering control system takes
   preventive action to obviate predicted unfavorable future network
   states.  It may also take perfective action to induce a more
   desirable state in the future.  In the reactive case, the control
   system responds correctively and perhaps adaptively to events that
   have already transpired in the network.

   The control dimension of Internet traffic engineering responds at
   multiple levels of temporal resolution to network events.  Certain
   aspects of capacity management, such as capacity planning, respond at
   very coarse temporal levels, ranging from days to possibly years.
   The introduction of automatically switched optical transport networks
   (e.g., based on the Multi-protocol Lambda Switching concepts) could
   significantly reduce the lifecycle for capacity planning by
   expediting provisioning of optical bandwidth.  Routing control
   functions operate at intermediate levels of temporal resolution,
   ranging from milliseconds to days.  Finally, the packet level
   processing functions (e.g., rate shaping, queue management, and
   scheduling) operate at very fine levels of temporal resolution,
   ranging from picoseconds to milliseconds while responding to the
   real-time statistical behavior of traffic.  The subsystems of
   Internet traffic engineering control include: capacity augmentation,
   routing control, traffic control, and resource control (including
   control of service policies at network elements).  When capacity is
   to be augmented for tactical purposes, it may be desirable to devise
   a deployment plan that expedites bandwidth provisioning while
   minimizing installation costs.

   Inputs into the traffic engineering control system include network
   state variables, policy variables, and decision variables.

   One major challenge of Internet traffic engineering is the
   realization of automated control capabilities that adapt quickly and
   cost effectively to significant changes in a network's state, while
   still maintaining stability.

   Another critical dimension of Internet traffic engineering is network
   performance evaluation, which is important for assessing the
   effectiveness of traffic engineering methods, and for monitoring and
   verifying compliance with network performance goals.  Results from
   performance evaluation can be used to identify existing problems,
   guide network re-optimization, and aid in the prediction of potential
   future problems.

   Performance evaluation can be achieved in many different ways.  The
   most notable techniques include analytical methods, simulation, and
   empirical methods based on measurements.  When analytical methods or
   simulation are used, network nodes and links can be modeled to
   capture relevant operational features such as topology, bandwidth,
   buffer space, and nodal service policies (link scheduling, packet
   prioritization, buffer management, etc.).  Analytical traffic models
   can be used to depict dynamic and behavioral traffic characteristics,
   such as burstiness, statistical distributions, and dependence.

   Performance evaluation can be quite complicated in practical network
   contexts.  A number of techniques can be used to simplify the
   analysis, such as abstraction, decomposition, and approximation.  For
   example, simplifying concepts such as effective bandwidth and
   effective buffer [Elwalid] may be used to approximate nodal behaviors
   at the packet level and simplify the analysis at the connection
   level.  Network analysis techniques using, for example, queuing
   models and approximation schemes based on asymptotic and
   decomposition techniques can render the analysis even more tractable.
   In particular, an emerging set of concepts known as network calculus
   [CRUZ] based on deterministic bounds may simplify network analysis
   relative to classical stochastic techniques.  When using analytical
   techniques, care should be taken to ensure that the models faithfully
   reflect the relevant operational characteristics of the modeled
   network entities.

   Simulation can be used to evaluate network performance or to verify
   and validate analytical approximations.  Simulation can, however, be
   computationally costly and may not always provide sufficient
   insights.  An appropriate approach to a given network performance
   evaluation problem may involve a hybrid combination of analytical
   techniques, simulation, and empirical methods.

   As a general rule, traffic engineering concepts and mechanisms must
   be sufficiently specific and well defined to address known
   requirements, but simultaneously flexible and extensible to
   accommodate unforeseen future demands.

1.2. Scope

   The scope of this document is intra-domain traffic engineering; that
   is, traffic engineering within a given autonomous system in the
   Internet.  This document will discuss concepts pertaining to intra-
   domain traffic control, including such issues as routing control,
   micro and macro resource allocation, and the control coordination
   problems that arise consequently.

   This document will describe and characterize techniques already in
   use or in advanced development for Internet traffic engineering.  The
   way these techniques fit together will be discussed and scenarios in
   which they are useful will be identified.

   While this document considers various intra-domain traffic
   engineering approaches, it focuses more on traffic engineering with
   MPLS.  Traffic engineering based upon manipulation of IGP metrics is
   not addressed in detail.  This topic may be addressed by other
   working group document(s).

   Although the emphasis is on intra-domain traffic engineering, in
   Section 7.0, an overview of the high level considerations pertaining
   to inter-domain traffic engineering will be provided.  Inter-domain
   Internet traffic engineering is crucial to the performance
   enhancement of the global Internet infrastructure.

   Whenever possible, relevant requirements from existing IETF documents
   and other sources will be incorporated by reference.

1.3 Terminology

   This subsection provides terminology which is useful for Internet
   traffic engineering.  The definitions presented apply to this
   document.  These terms may have other meanings elsewhere.

      - Baseline analysis:
            A study conducted to serve as a baseline for comparison to
            the actual behavior of the network.

      - Busy hour:
            A one hour period within a specified interval of time
            (typically 24 hours) in which the traffic load in a network
            or sub-network is greatest.

      - Bottleneck:
            A network element whose input traffic rate tends to be
            greater than its output rate.

      - Congestion:
            A state of a network resource in which the traffic incident
            on the resource exceeds its output capacity over an interval
            of time.

      - Congestion avoidance:
            An approach to congestion management that attempts to
            obviate the occurrence of congestion.

      - Congestion control:
            An approach to congestion management that attempts to remedy
            congestion problems that have already occurred.

      - Constraint-based routing:
            A class of routing protocols that take specified traffic
            attributes, network constraints, and policy constraints into
            account when making routing decisions.  Constraint-based
            routing is applicable to traffic aggregates as well as
            flows.  It is a generalization of QoS routing.

      - Demand side congestion management:
            A congestion management scheme that addresses congestion
            problems by regulating or conditioning offered load.

      - Effective bandwidth:
            The minimum amount of bandwidth that can be assigned to a
            flow or traffic aggregate in order to deliver 'acceptable
            service quality' to the flow or traffic aggregate.

      - Egress traffic:
            Traffic exiting a network or network element.

      - Hot-spot:
            A network element or subsystem which is in a state of
            congestion.

      - Ingress traffic:
            Traffic entering a network or network element.

      - Inter-domain traffic:
            Traffic that originates in one Autonomous system and
            terminates in another.

      - Loss network:
            A network that does not provide adequate buffering for
            traffic, so that traffic entering a busy resource within the
            network will be dropped rather than queued.

      - Metric:
            A parameter defined in terms of standard units of
            measurement.

      - Measurement Methodology:
            A repeatable measurement technique used to derive one or
            more metrics of interest.

      - Network Survivability:
            The capability to provide a prescribed level of QoS for
            existing services after a given number of failures occur
            within the network.

      - Offline traffic engineering:
            A traffic engineering system that exists outside of the
            network.

      - Online traffic engineering:
            A traffic engineering system that exists within the network,
            typically implemented on or as adjuncts to operational
            network elements.

      - Performance measures:
            Metrics that provide quantitative or qualitative measures of
            the performance of systems or subsystems of interest.

      - Performance management:
            A systematic approach to improving effectiveness in the
            accomplishment of specific networking goals related to
            performance improvement.

      - Performance Metric:
            A performance parameter defined in terms of standard units
            of measurement.

      - Provisioning:
            The process of assigning or configuring network resources to
            meet certain requests.

      - QoS routing:
            Class of routing systems that selects paths to be used by a
            flow based on the QoS requirements of the flow.

      - Service Level Agreement:
            A contract between a provider and a customer that guarantees
            specific levels of performance and reliability at a certain
            cost.

      - Stability:
            An operational state in which a network does not oscillate
            in a disruptive manner from one mode to another mode.

      - Supply side congestion management:
            A congestion management scheme that provisions additional
            network resources to address existing and/or anticipated
            congestion problems.

      - Transit traffic:
            Traffic whose origin and destination are both outside of the
            network under consideration.

      - Traffic characteristic:
            A description of the temporal behavior or a description of
            the attributes of a given traffic flow or traffic aggregate.

      - Traffic engineering system:
            A collection of objects, mechanisms, and protocols that are
            used conjunctively to accomplish traffic engineering
            objectives.

      - Traffic flow:
            A stream of packets between two end-points that can be
            characterized in a certain way.  A micro-flow has a more
            specific definition: A micro-flow is a stream of packets
            with the same source and destination addresses, source and
            destination ports, and protocol ID.

      - Traffic intensity:
            A measure of traffic loading with respect to a resource
            capacity over a specified period of time.  In classical
            telephony systems, traffic intensity is measured in units of
            Erlang.

      - Traffic matrix:
            A representation of the traffic demand between a set of
            origin and destination abstract nodes.  An abstract node can
            consist of one or more network elements.

      - Traffic monitoring:
            The process of observing traffic characteristics at a given
            point in a network and collecting the traffic information
            for analysis and further action.

      - Traffic trunk:
            An aggregation of traffic flows belonging to the same class
            which are forwarded through a common path.  A traffic trunk
            may be characterized by an ingress and egress node, and a
            set of attributes which determine its behavioral
            characteristics and requirements from the network.

2.0 Background

   The Internet has quickly evolved into a very critical communications
   infrastructure, supporting significant economic, educational, and
   social activities.  Simultaneously, the delivery of Internet
   communications services has become very competitive and end-users are
   demanding very high quality service from their service providers.
   Consequently, performance optimization of large scale IP networks,
   especially public Internet backbones, have become an important
   problem.  Network performance requirements are multi-dimensional,
   complex, and sometimes contradictory; making the traffic engineering
   problem very challenging.

   The network must convey IP packets from ingress nodes to egress nodes
   efficiently, expeditiously, and economically.  Furthermore, in a
   multiclass service environment (e.g., Diffserv capable networks), the
   resource sharing parameters of the network must be appropriately
   determined and configured according to prevailing policies and
   service models to resolve resource contention issues arising from
   mutual interference between packets traversing through the network.
   Thus, consideration must be given to resolving competition for
   network resources between traffic streams belonging to the same
   service class (intra-class contention resolution) and traffic streams
   belonging to different classes (inter-class contention resolution).

2.1 Context of Internet Traffic Engineering

   The context of Internet traffic engineering pertains to the scenarios
   where traffic engineering is used.  A traffic engineering methodology
   establishes appropriate rules to resolve traffic performance issues
   occurring in a specific context.  The context of Internet traffic
   engineering includes:

      (1)   A network context defining the universe of discourse, and in
            particular the situations in which the traffic engineering
            problems occur.  The network context includes network
            structure, network policies, network characteristics,
            network constraints, network quality attributes, and network
            optimization criteria.

      (2)   A problem context defining the general and concrete issues
            that traffic engineering addresses.  The problem context
            includes identification, abstraction of relevant features,
            representation, formulation, specification of the
            requirements on the solution space, and specification of the
            desirable features of acceptable solutions.

      (3)   A solution context suggesting how to address the issues
            identified by the problem context.  The solution context
            includes analysis, evaluation of alternatives, prescription,
            and resolution.

      (4)   An implementation and operational context in which the
            solutions are methodologically instantiated.  The
            implementation and operational context includes planning,
            organization, and execution.

   The context of Internet traffic engineering and the different problem
   scenarios are discussed in the following subsections.

2.2 Network Context

   IP networks range in size from small clusters of routers situated
   within a given location, to thousands of interconnected routers,
   switches, and other components distributed all over the world.

   Conceptually, at the most basic level of abstraction, an IP network
   can be represented as a distributed dynamical system consisting of:
   (1) a set of interconnected resources which provide transport
   services for IP traffic subject to certain constraints, (2) a demand
   system representing the offered load to be transported through the
   network, and (3) a response system consisting of network processes,
   protocols, and related mechanisms which facilitate the movement of
   traffic through the network [see also AWD2].

   The network elements and resources may have specific characteristics
   restricting the manner in which the demand is handled.  Additionally,
   network resources may be equipped with traffic control mechanisms
   superintending the way in which the demand is serviced.  Traffic
   control mechanisms may, for example, be used to control various
   packet processing activities within a given resource, arbitrate
   contention for access to the resource by different packets, and
   regulate traffic behavior through the resource.  A configuration
   management and provisioning system may allow the settings of the
   traffic control mechanisms to be manipulated by external or internal
   entities in order to exercise control over the way in which the
   network elements respond to internal and external stimuli.

   The details of how the network provides transport services for
   packets are specified in the policies of the network administrators
   and are installed through network configuration management and policy
   based provisioning systems.  Generally, the types of services
   provided by the network also depends upon the technology and
   characteristics of the network elements and protocols, the prevailing
   service and utility models, and the ability of the network
   administrators to translate policies into network configurations.

   Contemporary Internet networks have three significant
   characteristics:  (1) they provide real-time services, (2) they have
   become mission critical, and (3) their operating environments are
   very dynamic.  The dynamic characteristics of IP networks can be
   attributed in part to fluctuations in demand, to the interaction
   between various network protocols and processes, to the rapid
   evolution of the infrastructure which demands the constant inclusion
   of new technologies and new network elements, and to transient and
   persistent impairments which occur within the system.

   Packets contend for the use of network resources as they are conveyed
   through the network.  A network resource is considered to be
   congested if the arrival rate of packets exceed the output capacity
   of the resource over an interval of time.  Congestion may result in
   some of the arrival packets being delayed or even dropped.

   Congestion increases transit delays, delay variation, packet loss,
   and reduces the predictability of network services.  Clearly,
   congestion is a highly undesirable phenomenon.

   Combating congestion at a reasonable cost is a major objective of
   Internet traffic engineering.

   Efficient sharing of network resources by multiple traffic streams is
   a basic economic premise for packet switched networks in general and
   for the Internet in particular.  A fundamental challenge in network
   operation, especially in a large scale public IP network, is to
   increase the efficiency of resource utilization while minimizing the
   possibility of congestion.

   Increasingly, the Internet will have to function in the presence of
   different classes of traffic with different service requirements.
   The advent of Differentiated Services [RFC-2475] makes this
   requirement particularly acute.  Thus, packets may be grouped into
   behavior aggregates such that each behavior aggregate may have a
   common set of behavioral characteristics or a common set of delivery
   requirements.  In practice, the delivery requirements of a specific
   set of packets may be specified explicitly or implicitly.  Two of the
   most important traffic delivery requirements are capacity constraints
   and QoS constraints.

   Capacity constraints can be expressed statistically as peak rates,
   mean rates, burst sizes, or as some deterministic notion of effective
   bandwidth.  QoS requirements can be expressed in terms of (1)
   integrity constraints such as packet loss and (2) in terms of
   temporal constraints such as timing restrictions for the delivery of
   each packet (delay) and timing restrictions for the delivery of
   consecutive packets belonging to the same traffic stream (delay
   variation).

2.3 Problem Context

   Fundamental problems exist in association with the operation of a
   network described by the simple model of the previous subsection.
   This subsection reviews the problem context in relation to the
   traffic engineering function.

   The identification, abstraction, representation, and measurement of
   network features relevant to traffic engineering is a significant
   issue.

   One particularly important class of problems concerns how to
   explicitly formulate the problems that traffic engineering attempts
   to solve, how to identify the requirements on the solution space, how
   to specify the desirable features of good solutions, how to actually
   solve the problems, and how to measure and characterize the
   effectiveness of the solutions.

   Another class of problems concerns how to measure and estimate
   relevant network state parameters.  Effective traffic engineering
   relies on a good estimate of the offered traffic load as well as a
   view of the underlying topology and associated resource constraints.
   A network-wide view of the topology is also a must for offline
   planning.

   Still another class of problems concerns how to characterize the
   state of the network and how to evaluate its performance under a
   variety of scenarios.  The performance evaluation problem is two-
   fold.  One aspect of this problem relates to the evaluation of the
   system level performance of the network.  The other aspect relates to
   the evaluation of the resource level performance, which restricts
   attention to the performance analysis of individual network
   resources.  In this memo, we refer to the system level
   characteristics of the network as the "macro-states" and the resource
   level characteristics as the "micro-states." The system level
   characteristics are also known as the emergent properties of the
   network as noted earlier.  Correspondingly, we shall refer to the
   traffic engineering schemes dealing with network performance
   optimization at the systems level as "macro-TE" and the schemes that
   optimize at the individual resource level as "micro-TE."  Under
   certain circumstances, the system level performance can be derived
   from the resource level performance using appropriate rules of
   composition, depending upon the particular performance measures of
   interest.

   Another fundamental class of problems concerns how to effectively
   optimize network performance.  Performance optimization may entail
   translating solutions to specific traffic engineering problems into
   network configurations.  Optimization may also entail some degree of
   resource management control, routing control, and/or capacity
   augmentation.

   As noted previously, congestion is an undesirable phenomena in
   operational networks.  Therefore, the next subsection addresses the
   issue of congestion and its ramifications within the problem context
   of Internet traffic engineering.

2.3.1 Congestion and its Ramifications

   Congestion is one of the most significant problems in an operational
   IP context.  A network element is said to be congested if it
   experiences sustained overload over an interval of time.  Congestion
   almost always results in degradation of service quality to end users.
   Congestion control schemes can include demand side policies and
   supply side policies.  Demand side policies may restrict access to
   congested resources and/or dynamically regulate the demand to
   alleviate the overload situation.  Supply side policies may expand or
   augment network capacity to better accommodate offered traffic.
   Supply side policies may also re-allocate network resources by
   redistributing traffic over the infrastructure.  Traffic
   redistribution and resource re-allocation serve to increase the
   'effective capacity' seen by the demand.

   The emphasis of this memo is primarily on congestion management
   schemes falling within the scope of the network, rather than on
   congestion management systems dependent upon sensitivity and
   adaptivity from end-systems.  That is, the aspects that are
   considered in this memo with respect to congestion management are
   those solutions that can be provided by control entities operating on
   the network and by the actions of network administrators and network
   operations systems.

2.4 Solution Context

   The solution context for Internet traffic engineering involves
   analysis, evaluation of alternatives, and choice between alternative
   courses of action.  Generally the solution context is predicated on
   making reasonable inferences about the current or future state of the
   network, and subsequently making appropriate decisions that may
   involve a preference between alternative sets of action.  More
   specifically, the solution context demands reasonable estimates of
   traffic workload, characterization of network state, deriving
   solutions to traffic engineering problems which may be implicitly or
   explicitly formulated, and possibly instantiating a set of control
   actions.  Control actions may involve the manipulation of parameters
   associated with routing, control over tactical capacity acquisition,
   and control over the traffic management functions.

   The following list of instruments may be applicable to the solution
   context of Internet traffic engineering.

      (1)   A set of policies, objectives, and requirements (which may
            be context dependent) for network performance evaluation and
            performance  optimization.

      (2)   A collection of online and possibly offline tools and
            mechanisms for measurement, characterization, modeling, and
            control of Internet traffic and control over the placement
            and allocation of network resources, as well as control over
            the mapping or distribution of traffic onto the
            infrastructure.

      (3)   A set of constraints on the operating environment, the
            network protocols, and the traffic engineering system
            itself.

      (4)   A set of quantitative and qualitative techniques and
            methodologies for abstracting, formulating, and solving
            traffic engineering problems.

      (5)   A set of administrative control parameters which may be
            manipulated through a Configuration Management (CM) system.
            The CM system itself may include a configuration control
            subsystem, a configuration repository, a configuration
            accounting subsystem, and a configuration auditing
            subsystem.

      (6)   A set of guidelines for network performance evaluation,
            performance optimization, and performance improvement.

   Derivation of traffic characteristics through measurement and/or
   estimation is very useful within the realm of the solution space for
   traffic engineering.  Traffic estimates can be derived from customer
   subscription information, traffic projections, traffic models, and
   from actual empirical measurements.  The empirical measurements may
   be performed at the traffic aggregate level or at the flow level in
   order to derive traffic statistics at various levels of detail.
   Measurements at the flow level or on small traffic aggregates may be
   performed at edge nodes, where traffic enters and leaves the network.
   Measurements at large traffic aggregate levels may be performed
   within the core of the network where potentially numerous traffic
   flows may be in transit concurrently.

   To conduct performance studies and to support planning of existing
   and future networks, a routing analysis may be performed to determine
   the path(s) the routing protocols will choose for various traffic
   demands, and to ascertain the utilization of network resources as
   traffic is routed through the network.  The routing analysis should
   capture the selection of paths through the network, the assignment of

   traffic across multiple feasible routes, and the multiplexing of IP
   traffic over traffic trunks (if such constructs exists) and over the
   underlying network infrastructure.  A network topology model is a
   necessity for routing analysis.  A network topology model may be
   extracted from network architecture documents, from network designs,
   from information contained in router configuration files, from
   routing databases, from routing tables, or from automated tools that
   discover and depict network topology information.  Topology
   information may also be derived from servers that monitor network
   state, and from servers that perform provisioning functions.

   Routing in operational IP networks can be administratively controlled
   at various levels of abstraction including the manipulation of BGP
   attributes and manipulation of IGP metrics.  For path oriented
   technologies such as MPLS, routing can be further controlled by the
   manipulation of relevant traffic engineering parameters, resource
   parameters, and administrative policy constraints.  Within the
   context of MPLS, the path of an explicit label switched path (LSP)
   can be computed and established in various ways including: (1)
   manually, (2) automatically online using constraint-based routing
   processes implemented on label switching routers, and (3)
   automatically offline using constraint-based routing entities
   implemented on external traffic engineering support systems.

2.4.1 Combating the Congestion Problem

   Minimizing congestion is a significant aspect of Internet traffic
   engineering.  This subsection gives an overview of the general
   approaches that have been used or proposed to combat congestion
   problems.

   Congestion management policies can be categorized based upon the
   following criteria (see e.g., [YARE95] for a more detailed taxonomy
   of congestion control schemes): (1) Response time scale which can be
   characterized as long, medium, or short; (2) reactive versus
   preventive which relates to congestion control and congestion
   avoidance; and (3) supply side versus demand side congestion
   management schemes.  These aspects are discussed in the following
   paragraphs.

   (1) Congestion Management based on Response Time Scales

   - Long (weeks to months): Capacity planning works over a relatively
   long time scale to expand network capacity based on estimates or
   forecasts of future traffic demand and traffic distribution.  Since
   router and link provisioning take time and are generally expensive,
   these upgrades are typically carried out in the weeks-to-months or
   even years time scale.

   - Medium (minutes to days): Several control policies fall within the
   medium time scale category.  Examples include: (1) Adjusting IGP
   and/or BGP parameters to route traffic away or towards certain
   segments of the network; (2) Setting up and/or adjusting some
   explicitly routed label switched paths (ER-LSPs) in MPLS networks to
   route some traffic trunks away from possibly congested resources or
   towards possibly more favorable routes; (3) re-configuring the
   logical topology of the network to make it correlate more closely
   with the spatial traffic distribution using for example some
   underlying path-oriented technology such as MPLS LSPs, ATM PVCs, or
   optical channel trails.  Many of these adaptive medium time scale
   response schemes rely on a measurement system that monitors changes
   in traffic distribution, traffic shifts, and network resource
   utilization and subsequently provides feedback to the online and/or
   offline traffic engineering mechanisms and tools which employ this
   feedback information to trigger certain control actions to occur
   within the network.  The traffic engineering mechanisms and tools can
   be implemented in a distributed fashion or in a centralized fashion,
   and may have a hierarchical structure or a flat structure.  The
   comparative merits of distributed and centralized control structures
   for networks are well known.  A centralized scheme may have global
   visibility into the network state and may produce potentially more
   optimal solutions.  However, centralized schemes are prone to single
   points of failure and may not scale as well as distributed schemes.
   Moreover, the information utilized by a centralized scheme may be
   stale and may not reflect the actual state of the network.  It is not
   an objective of this memo to make a recommendation between
   distributed and centralized schemes.  This is a choice that network
   administrators must make based on their specific needs.

   - Short (picoseconds to minutes): This category includes packet level
   processing functions and events on the order of several round trip
   times.  It includes router mechanisms such as passive and active
   buffer management.  These mechanisms are used to control congestion
   and/or signal congestion to end systems so that they can adaptively
   regulate the rate at which traffic is injected into the network.  One
   of the most popular active queue management schemes, especially for
   TCP traffic, is Random Early Detection (RED) [FLJA93], which supports
   congestion avoidance by controlling the average queue size.  During
   congestion (but before the queue is filled), the RED scheme chooses
   arriving packets to "mark" according to a probabilistic algorithm
   which takes into account the average queue size.  For a router that
   does not utilize explicit congestion notification (ECN) see e.g.,
   [FLOY94], the marked packets can simply be dropped to signal the
   inception of congestion to end systems.  On the other hand, if the
   router supports ECN, then it can set the ECN field in the packet
   header.  Several variations of RED have been proposed to support
   different drop precedence levels in multi-class environments [RFC-

   2597], e.g., RED with In and Out (RIO) and Weighted RED.  There is
   general consensus that RED provides congestion avoidance performance
   which is not worse than traditional Tail-Drop (TD) queue management
   (drop arriving packets only when the queue is full).  Importantly,
   however, RED reduces the possibility of global synchronization and
   improves fairness among different TCP sessions.  However, RED by
   itself can not prevent congestion and unfairness caused by sources
   unresponsive to RED, e.g., UDP traffic and some misbehaved greedy
   connections.  Other schemes have been proposed to improve the
   performance and fairness in the presence of unresponsive traffic.
   Some of these schemes were proposed as theoretical frameworks and are
   typically not available in existing commercial products.  Two such
   schemes are Longest Queue Drop (LQD) and Dynamic Soft Partitioning
   with Random Drop (RND) [SLDC98].

   (2) Congestion Management: Reactive versus Preventive Schemes

   - Reactive: reactive (recovery) congestion management policies react
   to existing congestion problems to improve it.  All the policies
   described in the long and medium time scales above can be categorized
   as being reactive especially if the policies are based on monitoring
   and identifying existing congestion problems, and on the initiation
   of relevant actions to ease a situation.

   - Preventive: preventive (predictive/avoidance) policies take
   proactive action to prevent congestion based on estimates and
   predictions of future potential congestion problems.  Some of the
   policies described in the long and medium time scales fall into this
   category.  They do not necessarily respond immediately to existing
   congestion problems.  Instead forecasts of traffic demand and
   workload distribution are considered and action may be taken to
   prevent potential congestion problems in the future.  The schemes
   described in the short time scale (e.g., RED and its variations, ECN,
   LQD, and RND) are also used for congestion avoidance since dropping
   or marking packets before queues actually overflow would trigger
   corresponding TCP sources to slow down.

   (3) Congestion Management: Supply Side versus Demand Side Schemes

   - Supply side: supply side congestion management policies increase
   the effective capacity available to traffic in order to control or
   obviate congestion.  This can be accomplished by augmenting capacity.
   Another way to accomplish this is to minimize congestion by having a
   relatively balanced distribution of traffic over the network.  For
   example, capacity planning should aim to provide a physical topology
   and associated link bandwidths that match estimated traffic workload
   and traffic distribution based on forecasting (subject to budgetary
   and other constraints).  However, if actual traffic distribution does

   not match the topology derived from capacity panning (due to
   forecasting errors or facility constraints for example), then the
   traffic can be mapped onto the existing topology using routing
   control mechanisms, using path oriented technologies (e.g., MPLS LSPs
   and optical channel trails) to modify the logical topology, or by
   using some other load redistribution mechanisms.

   - Demand side: demand side congestion management policies control or
   regulate the offered traffic to alleviate congestion problems.  For
   example, some of the short time scale mechanisms described earlier
   (such as RED and its variations, ECN, LQD, and RND) as well as
   policing and rate shaping mechanisms attempt to regulate the offered
   load in various ways.  Tariffs may also be applied as a demand side
   instrument.  To date, however, tariffs have not been used as a means
   of demand side congestion management within the Internet.

   In summary, a variety of mechanisms can be used to address congestion
   problems in IP networks.  These mechanisms may operate at multiple
   time-scales.

2.5 Implementation and Operational Context

   The operational context of Internet traffic engineering is
   characterized by constant change which occur at multiple levels of
   abstraction.  The implementation context demands effective planning,
   organization, and execution.  The planning aspects may involve
   determining prior sets of actions to achieve desired objectives.
   Organizing involves arranging and assigning responsibility to the
   various components of the traffic engineering system and coordinating
   the activities to accomplish the desired TE objectives.  Execution
   involves measuring and applying corrective or perfective actions to
   attain and maintain desired TE goals.

3.0 Traffic Engineering Process Model(s)

   This section describes a generic process model that captures the high
   level practical aspects of Internet traffic engineering in an
   operational context.  The process model is described as a sequence of
   actions that a traffic engineer, or more generally a traffic
   engineering system, must perform to optimize the performance of an
   operational network (see also [RFC-2702, AWD2]).  The process model
   described here represents the broad activities common to most traffic
   engineering methodologies although the details regarding how traffic
   engineering is executed may differ from network to network.  This
   process model may be enacted explicitly or implicitly, by an
   automaton and/or by a human.

   The traffic engineering process model is iterative [AWD2].  The four
   phases of the process model described below are repeated continually.

   The first phase of the TE process model is to define the relevant
   control policies that govern the operation of the network.  These
   policies may depend upon many factors including the prevailing
   business model, the network cost structure, the operating
   constraints, the utility model, and optimization criteria.

   The second phase of the process model is a feedback mechanism
   involving the acquisition of measurement data from the operational
   network.  If empirical data is not readily available from the
   network, then synthetic workloads may be used instead which reflect
   either the prevailing or the expected workload of the network.
   Synthetic workloads may be derived by estimation or extrapolation
   using prior empirical data.  Their derivation may also be obtained
   using mathematical models of traffic characteristics or other means.

   The third phase of the process model is to analyze the network state
   and to characterize traffic workload.  Performance analysis may be
   proactive and/or reactive.  Proactive performance analysis identifies
   potential problems that do not exist, but could manifest in the
   future.  Reactive performance analysis identifies existing problems,
   determines their cause through diagnosis, and evaluates alternative
   approaches to remedy the problem, if necessary.  A number of
   quantitative and qualitative techniques may be used in the analysis
   process, including modeling based analysis and simulation.  The
   analysis phase of the process model may involve investigating the
   concentration and distribution of traffic across the network or
   relevant subsets of the network, identifying the characteristics of
   the offered traffic workload, identifying existing or potential
   bottlenecks, and identifying network pathologies such as ineffective
   link placement, single points of failures, etc.  Network pathologies
   may result from many factors including inferior network architecture,
   inferior network design, and configuration problems.  A traffic
   matrix may be constructed as part of the analysis process.  Network
   analysis may also be descriptive or prescriptive.

   The fourth phase of the TE process model is the performance
   optimization of the network.  The performance optimization phase
   involves a decision process which selects and implements a set of
   actions from a set of alternatives.  Optimization actions may include
   the use of appropriate techniques to either control the offered
   traffic or to control the distribution of traffic across the network.
   Optimization actions may also involve adding additional links or
   increasing link capacity, deploying additional hardware such as
   routers and switches, systematically adjusting parameters associated
   with routing such as IGP metrics and BGP attributes, and adjusting

   traffic management parameters.  Network performance optimization may
   also involve starting a network planning process to improve the
   network architecture, network design, network capacity, network
   technology, and the configuration of network elements to accommodate
   current and future growth.

3.1 Components of the Traffic Engineering Process Model

   The key components of the traffic engineering process model include a
   measurement subsystem, a modeling and analysis subsystem, and an
   optimization subsystem.  The following subsections examine these
   components as they apply to the traffic engineering process model.

3.2 Measurement

   Measurement is crucial to the traffic engineering function.  The
   operational state of a network can be conclusively determined only
   through measurement.  Measurement is also critical to the
   optimization function because it provides feedback data which is used
   by traffic engineering control subsystems.  This data is used to
   adaptively optimize network performance in response to events and
   stimuli originating within and outside the network.  Measurement is
   also needed to determine the quality of network services and to
   evaluate the effectiveness of traffic engineering policies.
   Experience suggests that measurement is most effective when acquired
   and applied systematically.

   When developing a measurement system to support the traffic
   engineering function in IP networks, the following questions should
   be carefully considered: Why is measurement needed in this particular
   context? What parameters are to be measured?  How should the
   measurement be accomplished?  Where should the measurement be
   performed? When should the measurement be performed?  How frequently
   should the monitored variables be measured?  What level of
   measurement accuracy and reliability is desirable? What level of
   measurement accuracy and reliability is realistically attainable? To
   what extent can the measurement system permissibly interfere with the
   monitored network components and variables? What is the acceptable
   cost of measurement? The answers to these questions will determine
   the measurement tools and methodologies appropriate in any given
   traffic engineering context.

   It should also be noted that there is a distinction between
   measurement and evaluation.  Measurement provides raw data concerning
   state parameters and variables of monitored network elements.
   Evaluation utilizes the raw data to make inferences regarding the
   monitored system.

   Measurement in support of the TE function can occur at different
   levels of abstraction.  For example, measurement can be used to
   derive packet level characteristics, flow level characteristics, user
   or customer level characteristics, traffic aggregate characteristics,
   component level characteristics, and network wide characteristics.

3.3 Modeling, Analysis, and Simulation

   Modeling and analysis are important aspects of Internet traffic
   engineering.  Modeling involves constructing an abstract or physical
   representation which depicts relevant traffic characteristics and
   network attributes.

   A network model is an abstract representation of the network which
   captures relevant network features, attributes, and characteristics,
   such as link and nodal attributes and constraints.  A network model
   may facilitate analysis and/or simulation which can be used to
   predict network performance under various conditions as well as to
   guide network expansion plans.

   In general, Internet traffic engineering models can be classified as
   either structural or behavioral.  Structural models focus on the
   organization of the network and its components.  Behavioral models
   focus on the dynamics of the network and the traffic workload.
   Modeling for Internet traffic engineering may also be formal or
   informal.

   Accurate behavioral models for traffic sources are particularly
   useful for analysis.  Development of behavioral traffic source models
   that are consistent with empirical data obtained from operational
   networks is a major research topic in Internet traffic engineering.
   These source models should also be tractable and amenable to
   analysis.  The topic of source models for IP traffic is a research
   topic and is therefore outside the scope of this document.  Its
   importance, however, must be emphasized.

   Network simulation tools are extremely useful for traffic
   engineering.  Because of the complexity of realistic quantitative
   analysis of network behavior, certain aspects of network performance
   studies can only be conducted effectively using simulation.  A good
   network simulator can be used to mimic and visualize network
   characteristics under various conditions in a safe and non-disruptive
   manner.  For example, a network simulator may be used to depict
   congested resources and hot spots, and to provide hints regarding
   possible solutions to network performance problems.  A good simulator
   may also be used to validate the effectiveness of planned solutions
   to network issues without the need to tamper with the operational
   network, or to commence an expensive network upgrade which may not

   achieve the desired objectives.  Furthermore, during the process of
   network planning, a network simulator may reveal pathologies such as
   single points of failure which may require additional redundancy, and
   potential bottlenecks and hot spots which may require additional
   capacity.

   Routing simulators are especially useful in large networks.  A
   routing simulator may identify planned links which may not actually
   be used to route traffic by the existing routing protocols.
   Simulators can also be used to conduct scenario based and
   perturbation based analysis, as well as sensitivity studies.
   Simulation results can be used to initiate appropriate actions in
   various ways.  For example, an important application of network
   simulation tools is to investigate and identify how best to make the
   network evolve and grow, in order to accommodate projected future
   demands.

3.4 Optimization

   Network performance optimization involves resolving network issues by
   transforming such issues into concepts that enable a solution,
   identification of a solution, and implementation of the solution.
   Network performance optimization can be corrective or perfective.  In
   corrective optimization, the goal is to remedy a problem that has
   occurred or that is incipient.  In perfective optimization, the goal
   is to improve network performance even when explicit problems do not
   exist and are not anticipated.

   Network performance optimization is a continual process, as noted
   previously.  Performance optimization iterations may consist of
   real-time optimization sub-processes and non-real-time network
   planning sub-processes.  The difference between real-time
   optimization and network planning is primarily in the relative time-
   scale in which they operate and in the granularity of actions.  One
   of the objectives of a real-time optimization sub-process is to
   control the mapping and distribution of traffic over the existing
   network infrastructure to avoid and/or relieve congestion, to assure
   satisfactory service delivery, and to optimize resource utilization.
   Real-time optimization is needed because random incidents such as
   fiber cuts or shifts in traffic demand will occur irrespective of how
   well a network is designed.  These incidents can cause congestion and
   other problems to manifest in an operational network.  Real-time
   optimization must solve such problems in small to medium time-scales
   ranging from micro-seconds to minutes or hours.  Examples of real-
   time optimization include queue management, IGP/BGP metric tuning,
   and using technologies such as MPLS explicit LSPs to change the paths
   of some traffic trunks [XIAO].

   One of the functions of the network planning sub-process is to
   initiate actions to systematically evolve the architecture,
   technology, topology, and capacity of a network.  When a problem
   exists in the network, real-time optimization should provide an
   immediate remedy.  Because a prompt response is necessary, the real-
   time solution may not be the best possible solution.  Network
   planning may subsequently be needed to refine the solution and
   improve the situation.  Network planning is also required to expand
   the network to support traffic growth and changes in traffic
   distribution over time.  As previously noted, a change in the
   topology and/or capacity of the network may be the outcome of network
   planning.

   Clearly, network planning and real-time performance optimization are
   mutually complementary activities.  A well-planned and designed
   network makes real-time optimization easier, while a systematic
   approach to real-time network performance optimization allows network
   planning to focus on long term issues rather than tactical
   considerations.  Systematic real-time network performance
   optimization also provides valuable inputs and insights toward
   network planning.

   Stability is an important consideration in real-time network
   performance optimization.  This aspect will be repeatedly addressed
   throughout this memo.

4.0 Historical Review and Recent Developments

   This section briefly reviews different traffic engineering approaches
   proposed and implemented in telecommunications and computer networks.
   The discussion is not intended to be comprehensive.  It is primarily
   intended to illuminate pre-existing perspectives and prior art
   concerning traffic engineering in the Internet and in legacy
   telecommunications networks.

4.1 Traffic Engineering in Classical Telephone Networks

   This subsection presents a brief overview of traffic engineering in
   telephone networks which often relates to the way user traffic is
   steered from an originating node to the terminating node.  This
   subsection presents a brief overview of this topic.  A detailed
   description of the various routing strategies applied in telephone
   networks is included in the book by G. Ash [ASH2].

   The early telephone network relied on static hierarchical routing,
   whereby routing patterns remained fixed independent of the state of
   the network or time of day.  The hierarchy was intended to
   accommodate overflow traffic, improve network reliability via

   alternate routes, and prevent call looping by employing strict
   hierarchical rules.  The network was typically over-provisioned since
   a given fixed route had to be dimensioned so that it could carry user
   traffic during a busy hour of any busy day.  Hierarchical routing in
   the telephony network was found to be too rigid upon the advent of
   digital switches and stored program control which were able to manage
   more complicated traffic engineering rules.

   Dynamic routing was introduced to alleviate the routing inflexibility
   in the static hierarchical routing so that the network would operate
   more efficiently.  This resulted in significant economic gains
   [HUSS87].  Dynamic routing typically reduces the overall loss
   probability by 10 to 20 percent (compared to static hierarchical
   routing).  Dynamic routing can also improve network resilience by
   recalculating routes on a per-call basis and periodically updating
   routes.

   There are three main types of dynamic routing in the telephone
   network.  They are time-dependent routing, state-dependent routing
   (SDR), and event dependent routing (EDR).

   In time-dependent routing, regular variations in traffic loads (such
   as time of day or day of week) are exploited in pre-planned routing
   tables.  In state-dependent routing, routing tables are updated
   online according to the current state of the network (e.g., traffic
   demand, utilization, etc.).  In event dependent routing, routing
   changes are incepted by events (such as call setups encountering
   congested or blocked links) whereupon new paths are searched out
   using learning models.  EDR methods are real-time adaptive, but they
   do not require global state information as does SDR.  Examples of EDR
   schemes include the dynamic alternate routing (DAR) from BT, the
   state-and-time dependent routing (STR) from NTT, and the success-to-
   the-top (STT) routing from AT&T.

   Dynamic non-hierarchical routing (DNHR) is an example of dynamic
   routing that was introduced in the AT&T toll network in the 1980's to
   respond to time-dependent information such as regular load variations
   as a function of time.  Time-dependent information in terms of load
   may be divided into three time scales: hourly, weekly, and yearly.
   Correspondingly, three algorithms are defined to pre-plan the routing
   tables.  The network design algorithm operates over a year-long
   interval while the demand servicing algorithm operates on a weekly
   basis to fine tune link sizes and routing tables to correct forecast
   errors on the yearly basis.  At the smallest time scale, the routing
   algorithm is used to make limited adjustments based on daily traffic
   variations.  Network design and demand servicing are computed using
   offline calculations.  Typically, the calculations require extensive
   searches on possible routes.  On the other hand, routing may need

   online calculations to handle crankback.  DNHR adopts a "two-link"
   approach whereby a path can consist of two links at most.  The
   routing algorithm presents an ordered list of route choices between
   an originating switch and a terminating switch.  If a call overflows,
   a via switch (a tandem exchange between the originating switch and
   the terminating switch) would send a crankback signal to the
   originating switch.  This switch would then select the next route,
   and so on, until there are no alternative routes available in which
   the call is blocked.

4.2 Evolution of Traffic Engineering in Packet Networks

   This subsection reviews related prior work that was intended to
   improve the performance of data networks.  Indeed, optimization of
   the performance of data networks started in the early days of the
   ARPANET.  Other early commercial networks such as SNA also recognized
   the importance of performance optimization and service
   differentiation.

   In terms of traffic management, the Internet has been a best effort
   service environment until recently.  In particular, very limited
   traffic management capabilities existed in IP networks to provide
   differentiated queue management and scheduling services to packets
   belonging to different classes.

   In terms of routing control, the Internet has employed distributed
   protocols for intra-domain routing.  These protocols are highly
   scalable and resilient.  However, they are based on simple algorithms
   for path selection which have very limited functionality to allow
   flexible control of the path selection process.

   In the following subsections, the evolution of practical traffic
   engineering mechanisms in IP networks and its predecessors are
   reviewed.

4.2.1 Adaptive Routing in the ARPANET

   The early ARPANET recognized the importance of adaptive routing where
   routing decisions were based on the current state of the network
   [MCQ80].  Early minimum delay routing approaches forwarded each
   packet to its destination along a path for which the total estimated
   transit time was the smallest.  Each node maintained a table of
   network delays, representing the estimated delay that a packet would
   experience along a given path toward its destination.  The minimum
   delay table was periodically transmitted by a node to its neighbors.
   The shortest path, in terms of hop count, was also propagated to give
   the connectivity information.

   One drawback to this approach is that dynamic link metrics tend to
   create "traffic magnets" causing congestion to be shifted from one
   location of a network to another location, resulting in oscillation
   and network instability.

4.2.2 Dynamic Routing in the Internet

   The Internet evolved from the APARNET and adopted dynamic routing
   algorithms with distributed control to determine the paths that
   packets should take en-route to their destinations.  The routing
   algorithms are adaptations of shortest path algorithms where costs
   are based on link metrics.  The link metric can be based on static or
   dynamic quantities.  The link metric based on static quantities may
   be assigned administratively according to local criteria.  The link
   metric based on dynamic quantities may be a function of a network
   congestion measure such as delay or packet loss.

   It was apparent early that static link metric assignment was
   inadequate because it can easily lead to unfavorable scenarios in
   which some links become congested while others remain lightly loaded.
   One of the many reasons for the inadequacy of static link metrics is
   that link metric assignment was often done without considering the
   traffic matrix in the network.  Also, the routing protocols did not
   take traffic attributes and capacity constraints into account when
   making routing decisions.  This results in traffic concentration
   being localized in subsets of the network infrastructure and
   potentially causing congestion.  Even if link metrics are assigned in
   accordance with the traffic matrix, unbalanced loads in the network
   can still occur due to a number factors including:

      -  Resources may not be deployed in the most optimal locations
         from a routing perspective.

      -  Forecasting errors in traffic volume and/or traffic
         distribution.

      -  Dynamics in traffic matrix due to the temporal nature of
         traffic patterns, BGP policy change from peers, etc.

   The inadequacy of the legacy Internet interior gateway routing system
   is one of the factors motivating the interest in path oriented
   technology with explicit routing and constraint-based routing
   capability such as MPLS.

4.2.3 ToS Routing

   Type-of-Service (ToS) routing involves different routes going to the
   same destination with selection dependent upon the ToS field of an IP
   packet [RFC-2474].  The ToS classes may be classified as low delay
   and high throughput.  Each link is associated with multiple link
   costs and each link cost is used to compute routes for a particular
   ToS.  A separate shortest path tree is computed for each ToS.  The
   shortest path algorithm must be run for each ToS resulting in very
   expensive computation.  Classical ToS-based routing is now outdated
   as the IP header field has been replaced by a Diffserv field.
   Effective traffic engineering is difficult to perform in classical
   ToS-based routing because each class still relies exclusively on
   shortest path routing which results in localization of traffic
   concentration within the network.

4.2.4 Equal Cost Multi-Path

   Equal Cost Multi-Path (ECMP) is another technique that attempts to
   address the deficiency in the Shortest Path First (SPF) interior
   gateway routing systems [RFC-2328].  In the classical SPF algorithm,
   if two or more shortest paths exist to a given destination, the
   algorithm will choose one of them.  The algorithm is modified
   slightly in ECMP so that if two or more equal cost shortest paths
   exist between two nodes, the traffic between the nodes is distributed
   among the multiple equal-cost paths.  Traffic distribution across the
   equal-cost paths is usually performed in one of two ways: (1)
   packet-based in a round-robin fashion, or (2) flow-based using
   hashing on source and destination IP addresses and possibly other
   fields of the IP header.  The first approach can easily cause out-
   of-order packets while the second approach is dependent upon the
   number and distribution of flows.  Flow-based load sharing may be
   unpredictable in an enterprise network where the number of flows is
   relatively small and less heterogeneous (for example, hashing may not
   be uniform), but it is generally effective in core public networks
   where the number of flows is large and heterogeneous.

   In ECMP, link costs are static and bandwidth constraints are not
   considered, so ECMP attempts to distribute the traffic as equally as
   possible among the equal-cost paths independent of the congestion
   status of each path.  As a result, given two equal-cost paths, it is
   possible that one of the paths will be more congested than the other.
   Another drawback of ECMP is that load sharing cannot be achieved on
   multiple paths which have non-identical costs.

4.2.5 Nimrod

   Nimrod is a routing system developed to provide heterogeneous service
   specific routing in the Internet, while taking multiple constraints
   into account [RFC-1992].  Essentially, Nimrod is a link state routing
   protocol which supports path oriented packet forwarding.  It uses the
   concept of maps to represent network connectivity and services at
   multiple levels of abstraction.  Mechanisms are provided to allow
   restriction of the distribution of routing information.

   Even though Nimrod did not enjoy deployment in the public Internet, a
   number of key concepts incorporated into the Nimrod architecture,
   such as explicit routing which allows selection of paths at
   originating nodes, are beginning to find applications in some recent
   constraint-based routing initiatives.

4.3 Overlay Model

   In the overlay model, a virtual-circuit network, such as ATM, frame
   relay, or WDM, provides virtual-circuit connectivity between routers
   that are located at the edges of a virtual-circuit cloud.  In this
   mode, two routers that are connected through a virtual circuit see a
   direct adjacency between themselves independent of the physical route
   taken by the virtual circuit through the ATM, frame relay, or WDM
   network.  Thus, the overlay model essentially decouples the logical
   topology that routers see from the physical topology that the ATM,
   frame relay, or WDM network manages.  The overlay model based on ATM
   or frame relay enables a network administrator or an automaton to
   employ traffic engineering concepts to perform path optimization by
   re-configuring or rearranging the virtual circuits so that a virtual
   circuit on a congested or sub-optimal physical link can be re-routed
   to a less congested or more optimal one.  In the overlay model,
   traffic engineering is also employed to establish relationships
   between the traffic management parameters (e.g., PCR, SCR, and MBS
   for ATM) of the virtual-circuit technology and the actual traffic
   that traverses each circuit.  These relationships can be established
   based upon known or projected traffic profiles, and some other
   factors.

   The overlay model using IP over ATM requires the management of two
   separate networks with different technologies (IP and ATM) resulting
   in increased operational complexity and cost.  In the fully-meshed
   overlay model, each router would peer to every other router in the
   network, so that the total number of adjacencies is a quadratic
   function of the number of routers.  Some of the issues with the
   overlay model are discussed in [AWD2].

4.4 Constrained-Based Routing

   Constraint-based routing refers to a class of routing systems that
   compute routes through a network subject to the satisfaction of a set
   of constraints and requirements.  In the most general setting,
   constraint-based routing may also seek to optimize overall network
   performance while minimizing costs.

   The constraints and requirements may be imposed by the network itself
   or by administrative policies.  Constraints may include bandwidth,
   hop count, delay, and policy instruments such as resource class
   attributes.  Constraints may also include domain specific attributes
   of certain network technologies and contexts which impose
   restrictions on the solution space of the routing function.  Path
   oriented technologies such as MPLS have made constraint-based routing
   feasible and attractive in public IP networks.

   The concept of constraint-based routing within the context of MPLS
   traffic engineering requirements in IP networks was first defined in
   [RFC-2702].

   Unlike QoS routing (for example, see [RFC-2386] and [MA]) which
   generally addresses the issue of routing individual traffic flows to
   satisfy prescribed flow based QoS requirements subject to network
   resource availability, constraint-based routing is applicable to
   traffic aggregates as well as flows and may be subject to a wide
   variety of constraints which may include policy restrictions.

4.5 Overview of Other IETF Projects Related to Traffic Engineering

   This subsection reviews a number of IETF activities pertinent to
   Internet traffic engineering.  These activities are primarily
   intended to evolve the IP architecture to support new service
   definitions which allow preferential or differentiated treatment to
   be accorded to certain types of traffic.

4.5.1 Integrated Services

   The IETF Integrated Services working group developed the integrated
   services (Intserv) model.  This model requires resources, such as
   bandwidth and buffers, to be reserved a priori for a given traffic
   flow to ensure that the quality of service requested by the traffic
   flow is satisfied.  The integrated services model includes additional
   components beyond those used in the best-effort model such as packet
   classifiers, packet schedulers, and admission control.  A packet
   classifier is used to identify flows that are to receive a certain
   level of service.  A packet scheduler handles the scheduling of

   service to different packet flows to ensure that QoS commitments are
   met.  Admission control is used to determine whether a router has the
   necessary resources to accept a new flow.

   Two services have been defined under the Integrated Services model:
   guaranteed service [RFC-2212] and controlled-load service [RFC-2211].

   The guaranteed service can be used for applications requiring bounded
   packet delivery time.  For this type of application, data that is
   delivered to the application after a pre-defined amount of time has
   elapsed is usually considered worthless.  Therefore, guaranteed
   service was intended to provide a firm quantitative bound on the
   end-to-end packet delay for a flow.  This is accomplished by
   controlling the queuing delay on network elements along the data flow
   path.  The guaranteed service model does not, however, provide
   bounds on jitter (inter-arrival times between consecutive packets).

   The controlled-load service can be used for adaptive applications
   that can tolerate some delay but are sensitive to traffic overload
   conditions.  This type of application typically functions
   satisfactorily when the network is lightly loaded but its performance
   degrades significantly when the network is heavily loaded.
   Controlled-load service, therefore, has been designed to provide
   approximately the same service as best-effort service in a lightly
   loaded network regardless of actual network conditions.  Controlled-
   load service is described qualitatively in that no target values of
   delay or loss are specified.

   The main issue with the Integrated Services model has been
   scalability [RFC-2998], especially in large public IP networks which
   may potentially have millions of active micro-flows in transit
   concurrently.

   A notable feature of the Integrated Services model is that it
   requires explicit signaling of QoS requirements from end systems to
   routers [RFC-2753].  The Resource Reservation Protocol (RSVP)
   performs this signaling function and is a critical component of the
   Integrated Services model.  The RSVP protocol is described next.

4.5.2 RSVP

   RSVP is a soft state signaling protocol [RFC-2205].  It supports
   receiver initiated establishment of resource reservations for both
   multicast and unicast flows.  RSVP was originally developed as a
   signaling protocol within the integrated services framework for
   applications to communicate QoS requirements to the network and for
   the network to reserve relevant resources to satisfy the QoS
   requirements [RFC-2205].

   Under RSVP, the sender or source node sends a PATH message to the
   receiver with the same source and destination addresses as the
   traffic which the sender will generate.  The PATH message contains:
   (1) a sender Tspec specifying the characteristics of the traffic, (2)
   a sender Template specifying the format of the traffic, and (3) an
   optional Adspec which is used to support the concept of one pass with
   advertising" (OPWA) [RFC-2205].  Every intermediate router along the
   path forwards the PATH Message to the next hop determined by the
   routing protocol.  Upon receiving a PATH Message, the receiver
   responds with a RESV message which includes a flow descriptor used to
   request resource reservations.  The RESV message travels to the
   sender or source node in the opposite direction along the path that
   the PATH message traversed.  Every intermediate router along the path
   can reject or accept the reservation request of the RESV message.  If
   the request is rejected, the rejecting router will send an error
   message to the receiver and the signaling process will terminate.  If
   the request is accepted, link bandwidth and buffer space are
   allocated for the flow and the related flow state information is
   installed in the router.

   One of the issues with the original RSVP specification was
   Scalability.  This is because reservations were required for micro-
   flows, so that the amount of state maintained by network elements
   tends to increase linearly with the number of micro-flows.  These
   issues are described in [RFC-2961].

   Recently, RSVP has been modified and extended in several ways to
   mitigate the scaling problems.  As a result, it is becoming a
   versatile signaling protocol for the Internet.  For example, RSVP has
   been extended to reserve resources for aggregation of flows, to set
   up MPLS explicit label switched paths, and to perform other signaling
   functions within the Internet.  There are also a number of proposals
   to reduce the amount of refresh messages required to maintain
   established RSVP sessions [RFC-2961].

   A number of IETF working groups have been engaged in activities
   related to the RSVP protocol.  These include the original RSVP
   working group, the MPLS working group, the Resource Allocation
   Protocol working group, and the Policy Framework working group.

4.5.3 Differentiated Services

   The goal of the Differentiated Services (Diffserv) effort within the
   IETF is to devise scalable mechanisms for categorization of traffic
   into behavior aggregates, which ultimately allows each behavior
   aggregate to be treated differently, especially when there is a
   shortage of resources such as link bandwidth and buffer space [RFC-
   2475].  One of the primary motivations for the Diffserv effort was to

   devise alternative mechanisms for service differentiation in the
   Internet that mitigate the scalability issues encountered with the
   Intserv model.

   The IETF Diffserv working group has defined a Differentiated Services
   field in the IP header (DS field).  The DS field consists of six bits
   of the part of the IP header formerly known as TOS octet.  The DS
   field is used to indicate the forwarding treatment that a packet
   should receive at a node [RFC-2474].  The Diffserv working group has
   also standardized a number of Per-Hop Behavior (PHB) groups.  Using
   the PHBs, several classes of services can be defined using different
   classification, policing, shaping, and scheduling rules.

   For an end-user of network services to receive Differentiated
   Services from its Internet Service Provider (ISP), it may be
   necessary for the user to have a Service Level Agreement (SLA) with
   the ISP.  An SLA may explicitly or implicitly specify a Traffic
   Conditioning Agreement (TCA) which defines classifier rules as well
   as metering, marking, discarding, and shaping rules.

   Packets are classified, and possibly policed and shaped at the
   ingress to a Diffserv network.  When a packet traverses the boundary
   between different Diffserv domains, the DS field of the packet may be
   re-marked according to existing agreements between the domains.

   Differentiated Services allows only a finite number of service
   classes to be indicated by the DS field.  The main advantage of the
   Diffserv approach relative to the Intserv model is scalability.
   Resources are allocated on a per-class basis and the amount of state
   information is proportional to the number of classes rather than to
   the number of application flows.

   It should be obvious from the previous discussion that the Diffserv
   model essentially deals with traffic management issues on a per hop
   basis.  The Diffserv control model consists of a collection of
   micro-TE control mechanisms.  Other traffic engineering capabilities,
   such as capacity management (including routing control), are also
   required in order to deliver acceptable service quality in Diffserv
   networks.  The concept of Per Domain Behaviors has been introduced to
   better capture the notion of differentiated services across a
   complete domain [RFC-3086].

4.5.4 MPLS

   MPLS is an advanced forwarding scheme which also includes extensions
   to conventional IP control plane protocols.  MPLS extends the
   Internet routing model and enhances packet forwarding and path
   control [RFC-3031].

   At the ingress to an MPLS domain, label switching routers (LSRs)
   classify IP packets into forwarding equivalence classes (FECs) based
   on a variety of factors, including, e.g., a combination of the
   information carried in the IP header of the packets and the local
   routing information maintained by the LSRs.  An MPLS label is then
   prepended to each packet according to their forwarding equivalence
   classes.  In a non-ATM/FR environment, the label is 32 bits long and
   contains a 20-bit label field, a 3-bit experimental field (formerly
   known as Class-of-Service or CoS field), a 1-bit label stack
   indicator and an 8-bit TTL field.  In an ATM (FR) environment, the
   label consists of information encoded in the VCI/VPI (DLCI) field.
   An MPLS capable router (an LSR) examines the label and possibly the
   experimental field and uses this information to make packet
   forwarding decisions.

   An LSR makes forwarding decisions by using the label prepended to
   packets as the index into a local next hop label forwarding entry
   (NHLFE).  The packet is then processed as specified in the NHLFE.
   The incoming label may be replaced by an outgoing label, and the
   packet may be switched to the next LSR.  This label-switching process
   is very similar to the label (VCI/VPI) swapping process in ATM
   networks.  Before a packet leaves an MPLS domain, its MPLS label may
   be removed.  A Label Switched Path (LSP) is the path between an
   ingress LSRs and an egress LSRs through which a labeled packet
   traverses.  The path of an explicit LSP is defined at the originating
   (ingress) node of the LSP.  MPLS can use a signaling protocol such as
   RSVP or LDP to set up LSPs.

   MPLS is a very powerful technology for Internet traffic engineering
   because it supports explicit LSPs which allow constraint-based
   routing to be implemented efficiently in IP networks [AWD2].  The
   requirements for traffic engineering over MPLS are described in
   [RFC-2702].  Extensions to RSVP to support instantiation of explicit
   LSP are discussed in [RFC-3209].  Extensions to LDP, known as CR-LDP,
   to support explicit LSPs are presented in [JAM].

4.5.5 IP Performance Metrics

   The IETF IP Performance Metrics (IPPM) working group has been
   developing a set of standard metrics that can be used to monitor the
   quality, performance, and reliability of Internet services.  These
   metrics can be applied by network operators, end-users, and
   independent testing groups to provide users and service providers
   with a common understanding of the performance and reliability of the
   Internet component 'clouds' they use/provide [RFC-2330].  The
   criteria for performance metrics developed by the IPPM WG are
   described in [RFC-2330].  Examples of performance metrics include
   one-way packet

   loss [RFC-2680], one-way delay [RFC-2679], and connectivity measures
   between two nodes [RFC-2678].  Other metrics include second-order
   measures of packet loss and delay.

   Some of the performance metrics specified by the IPPM WG are useful
   for specifying Service Level Agreements (SLAs).  SLAs are sets of
   service level objectives negotiated between users and service
   providers, wherein each objective is a combination of one or more
   performance metrics, possibly subject to certain constraints.

4.5.6 Flow Measurement

   The IETF Real Time Flow Measurement (RTFM) working group has produced
   an architecture document defining a method to specify traffic flows
   as well as a number of components for flow measurement (meters, meter
   readers, manager) [RFC-2722].  A flow measurement system enables
   network traffic flows to be measured and analyzed at the flow level
   for a variety of purposes.  As noted in RFC 2722, a flow measurement
   system can be very useful in the following contexts: (1)
   understanding the behavior of existing networks, (2) planning for
   network development and expansion, (3) quantification of network
   performance, (4) verifying the quality of network service, and (5)
   attribution of network usage to users.

   A flow measurement system consists of meters, meter readers, and
   managers.  A meter observes packets passing through a measurement
   point, classifies them into certain groups, accumulates certain usage
   data (such as the number of packets and bytes for each group), and
   stores the usage data in a flow table.  A group may represent a user
   application, a host, a network, a group of networks, etc.  A meter
   reader gathers usage data from various meters so it can be made
   available for analysis.  A manager is responsible for configuring and
   controlling meters and meter readers.  The instructions received by a
   meter from a manager include flow specification, meter control
   parameters, and sampling techniques.  The instructions received by a
   meter reader from a manager include the address of the meter whose
   date is to be collected, the frequency of data collection, and the
   types of flows to be collected.

4.5.7 Endpoint Congestion Management

   [RFC-3124] is intended to provide a set of congestion control
   mechanisms that transport protocols can use.  It is also intended to
   develop mechanisms for unifying congestion control across a subset of
   an endpoint's active unicast connections (called a congestion group).
   A congestion manager continuously monitors the state of the path for

   each congestion group under its control.  The manager uses that
   information to instruct a scheduler on how to partition bandwidth
   among the connections of that congestion group.

4.6 Overview of ITU Activities Related to Traffic Engineering

   This section provides an overview of prior work within the ITU-T
   pertaining to traffic engineering in traditional telecommunications
   networks.

   ITU-T Recommendations E.600 [ITU-E600], E.701 [ITU-E701], and E.801
   [ITU-E801] address traffic engineering issues in traditional
   telecommunications networks.  Recommendation E.600 provides a
   vocabulary for describing traffic engineering concepts, while E.701
   defines reference connections, Grade of Service (GOS), and traffic
   parameters for ISDN.  Recommendation E.701 uses the concept of a
   reference connection to identify representative cases of different
   types of connections without describing the specifics of their actual
   realizations by different physical means.  As defined in
   Recommendation E.600, "a connection is an association of resources
   providing means for communication between two or more devices in, or
   attached to, a telecommunication network."  Also, E.600 defines "a
   resource as any set of physically or conceptually identifiable
   entities within a telecommunication network, the use of which can be
   unambiguously determined" [ITU-E600].  There can be different types
   of connections as the number and types of resources in a connection
   may vary.

   Typically, different network segments are involved in the path of a
   connection.  For example, a connection may be local, national, or
   international.  The purposes of reference connections are to clarify
   and specify traffic performance issues at various interfaces between
   different network domains.  Each domain may consist of one or more
   service provider networks.

   Reference connections provide a basis to define grade of service
   (GoS) parameters related to traffic engineering within the ITU-T
   framework.  As defined in E.600, "GoS refers to a number of traffic
   engineering variables which are used to provide a measure of the
   adequacy of a group of resources under specified conditions."  These
   GoS variables may be probability of loss, dial tone, delay, etc.
   They are essential for network internal design and operation as well
   as for component performance specification.

   GoS is different from quality of service (QoS) in the ITU framework.
   QoS is the performance perceivable by a telecommunication service
   user and expresses the user's degree of satisfaction of the service.
   QoS parameters focus on performance aspects observable at the service

   access points and network interfaces, rather than their causes within
   the network.  GoS, on the other hand, is a set of network oriented
   measures which characterize the adequacy of a group of resources
   under specified conditions.  For a network to be effective in serving
   its users, the values of both GoS and QoS parameters must be related,
   with GoS parameters typically making a major contribution to the QoS.

   Recommendation E.600 stipulates that a set of GoS parameters must be
   selected and defined on an end-to-end basis for each major service
   category provided by a network to assist the network provider with
   improving efficiency and effectiveness of the network.  Based on a
   selected set of reference connections, suitable target values are
   assigned to the selected GoS parameters under normal and high load
   conditions.  These end-to-end GoS target values are then apportioned
   to individual resource components of the reference connections for
   dimensioning purposes.

4.7 Content Distribution

   The Internet is dominated by client-server interactions, especially
   Web traffic (in the future, more sophisticated media servers may
   become dominant).  The location and performance of major information
   servers has a significant impact on the traffic patterns within the
   Internet as well as on the perception of service quality by end
   users.

   A number of dynamic load balancing techniques have been devised to
   improve the performance of replicated information servers.  These
   techniques can cause spatial traffic characteristics to become more
   dynamic in the Internet because information servers can be
   dynamically picked based upon the location of the clients, the
   location of the servers, the relative utilization of the servers, the
   relative performance of different networks, and the relative
   performance of different parts of a network.  This process of
   assignment of distributed servers to clients is called Traffic
   Directing.  It functions at the application layer.

   Traffic Directing schemes that allocate servers in multiple
   geographically dispersed locations to clients may require empirical
   network performance statistics to make more effective decisions.  In
   the future, network measurement systems may need to provide this type
   of information.  The exact parameters needed are not yet defined.

   When congestion exists in the network, Traffic Directing and Traffic
   Engineering systems should act in a coordinated manner.  This topic
   is for further study.

   The issues related to location and replication of information
   servers, particularly web servers, are important for Internet traffic
   engineering because these servers contribute a substantial proportion
   of Internet traffic.

5.0 Taxonomy of Traffic Engineering Systems

   This section presents a short taxonomy of traffic engineering
   systems.  A taxonomy of traffic engineering systems can be
   constructed based on traffic engineering styles and views as listed
   below:

      - Time-dependent vs State-dependent vs Event-dependent
      - Offline vs Online
      - Centralized vs Distributed
      - Local vs Global Information
      - Prescriptive vs Descriptive
      - Open Loop vs Closed Loop
      - Tactical vs Strategic

   These classification systems are described in greater detail in the
   following subsections of this document.

5.1 Time-Dependent Versus State-Dependent Versus Event Dependent

   Traffic engineering methodologies can be classified as time-
   dependent, or state-dependent, or event-dependent.  All TE schemes
   are considered to be dynamic in this document.  Static TE implies
   that no traffic engineering methodology or algorithm is being
   applied.

   In the time-dependent TE, historical information based on periodic
   variations in traffic, (such as time of day), is used to pre-program
   routing plans and other TE control mechanisms.  Additionally,
   customer subscription or traffic projection may be used.  Pre-
   programmed routing plans typically change on a relatively long time
   scale (e.g., diurnal).  Time-dependent algorithms do not attempt to
   adapt to random variations in traffic or changing network conditions.
   An example of a time-dependent algorithm is a global centralized
   optimizer where the input to the system is a traffic matrix and
   multi-class QoS requirements as described [MR99].

   State-dependent TE adapts the routing plans for packets based on the
   current state of the network.  The current state of the network
   provides additional information on variations in actual traffic
   (i.e., perturbations from regular variations) that could not be
   predicted using historical information.  Constraint-based routing is

   an example of state-dependent TE operating in a relatively long time
   scale.  An example operating in a relatively short time scale is a
   load-balancing algorithm described in [MATE].

   The state of the network can be based on parameters such as
   utilization, packet delay, packet loss, etc.  These parameters can be
   obtained in several ways.  For example, each router may flood these
   parameters periodically or by means of some kind of trigger to other
   routers.  Another approach is for a particular router performing
   adaptive TE to send probe packets along a path to gather the state of
   that path.  Still another approach is for a management system to
   gather relevant information from network elements.

   Expeditious and accurate gathering and distribution of state
   information is critical for adaptive TE due to the dynamic nature of
   network conditions.  State-dependent algorithms may be applied to
   increase network efficiency and resilience.  Time-dependent
   algorithms are more suitable for predictable traffic variations.  On
   the other hand, state-dependent algorithms are more suitable for
   adapting to the prevailing network state.

   Event-dependent TE methods can also be used for TE path selection.
   Event-dependent TE methods are distinct from time-dependent and
   state-dependent TE methods in the manner in which paths are selected.
   These algorithms are adaptive and distributed in nature and typically
   use learning models to find good paths for TE in a network.  While
   state-dependent TE models typically use available-link-bandwidth
   (ALB) flooding for TE path selection, event-dependent TE methods do
   not require ALB flooding.  Rather, event-dependent TE methods
   typically search out capacity by learning models, as in the success-
   to-the-top (STT) method.  ALB flooding can be resource intensive,
   since it requires link bandwidth to carry LSAs, processor capacity to
   process LSAs, and the overhead can limit area/autonomous system (AS)
   size.  Modeling results suggest that event-dependent TE methods could
   lead to a reduction in ALB flooding overhead without loss of network
   throughput performance [ASH3].

5.2 Offline Versus Online

   Traffic engineering requires the computation of routing plans.  The
   computation may be performed offline or online.  The computation can
   be done offline for scenarios where routing plans need not be
   executed in real-time.  For example, routing plans computed from
   forecast information may be computed offline.  Typically, offline
   computation is also used to perform extensive searches on multi-
   dimensional solution spaces.

   Online computation is required when the routing plans must adapt to
   changing network conditions as in state-dependent algorithms.  Unlike
   offline computation (which can be computationally demanding), online
   computation is geared toward relative simple and fast calculations to
   select routes, fine-tune the allocations of resources, and perform
   load balancing.

5.3 Centralized Versus Distributed

   Centralized control has a central authority which determines routing
   plans and perhaps other TE control parameters on behalf of each
   router.  The central authority collects the network-state information
   from all routers periodically and returns the routing information to
   the routers.  The routing update cycle is a critical parameter
   directly impacting the performance of the network being controlled.
   Centralized control may need high processing power and high bandwidth
   control channels.

   Distributed control determines route selection by each router
   autonomously based on the routers view of the state of the network.
   The network state information may be obtained by the router using a
   probing method or distributed by other routers on a periodic basis
   using link state advertisements.  Network state information may also
   be disseminated under exceptional conditions.

5.4 Local Versus Global

   Traffic engineering algorithms may require local or global network-
   state information.

   Local information pertains to the state of a portion of the domain.
   Examples include the bandwidth and packet loss rate of a particular
   path.  Local state information may be sufficient for certain
   instances of distributed-controlled TEs.

   Global information pertains to the state of the entire domain
   undergoing traffic engineering.  Examples include a global traffic
   matrix and loading information on each link throughout the domain of
   interest.  Global state information is typically required with
   centralized control.  Distributed TE systems may also need global
   information in some cases.

5.5 Prescriptive Versus Descriptive

TE systems may also be classified as prescriptive or descriptive.

   Prescriptive traffic engineering evaluates alternatives and
   recommends a course of action.  Prescriptive traffic engineering can
   be further categorized as either corrective or perfective.
   Corrective TE prescribes a course of action to address an existing or
   predicted anomaly.  Perfective TE prescribes a course of action to
   evolve and improve network performance even when no anomalies are
   evident.

   Descriptive traffic engineering, on the other hand, characterizes the
   state of the network and assesses the impact of various policies
   without recommending any particular course of action.

5.6 Open-Loop Versus Closed-Loop

   Open-loop traffic engineering control is where control action does
   not use feedback information from the current network state.  The
   control action may use its own local information for accounting
   purposes, however.

   Closed-loop traffic engineering control is where control action
   utilizes feedback information from the network state.  The feedback
   information may be in the form of historical information or current
   measurement.

5.7 Tactical vs Strategic

   Tactical traffic engineering aims to address specific performance
   problems (such as hot-spots) that occur in the network from a
   tactical perspective, without consideration of overall strategic
   imperatives.  Without proper planning and insights, tactical TE tends
   to be ad hoc in nature.

   Strategic traffic engineering approaches the TE problem from a more
   organized and systematic perspective, taking into consideration the
   immediate and longer term consequences of specific policies and
   actions.

6.0 Recommendations for Internet Traffic Engineering

   This section describes high level recommendations for traffic
   engineering in the Internet.  These recommendations are presented in
   general terms.

   The recommendations describe the capabilities needed to solve a
   traffic engineering problem or to achieve a traffic engineering
   objective.  Broadly speaking, these recommendations can be
   categorized as either functional and non-functional recommendations.

   Functional recommendations for Internet traffic engineering describe
   the functions that a traffic engineering system should perform.
   These functions are needed to realize traffic engineering objectives
   by addressing traffic engineering problems.

   Non-functional recommendations for Internet traffic engineering
   relate to the quality attributes or state characteristics of a
   traffic engineering system.  These recommendations may contain
   conflicting assertions and may sometimes be difficult to quantify
   precisely.

6.1 Generic Non-functional Recommendations

   The generic non-functional recommendations for Internet traffic
   engineering include: usability, automation, scalability, stability,
   visibility, simplicity, efficiency, reliability, correctness,
   maintainability, extensibility, interoperability, and security.  In a
   given context, some of these recommendations may be critical while
   others may be optional.  Therefore, prioritization may be required
   during the development phase of a traffic engineering system (or
   components thereof) to tailor it to a specific operational context.

   In the following paragraphs, some of the aspects of the non-
   functional recommendations for Internet traffic engineering are
   summarized.

   Usability: Usability is a human factor aspect of traffic engineering
   systems.  Usability refers to the ease with which a traffic
   engineering system can be deployed and operated.  In general, it is
   desirable to have a TE system that can be readily deployed in an
   existing network.  It is also desirable to have a TE system that is
   easy to operate and maintain.

   Automation: Whenever feasible, a traffic engineering system should
   automate as many traffic engineering functions as possible to
   minimize the amount of human effort needed to control and analyze
   operational networks.  Automation is particularly imperative in large
   scale public networks because of the high cost of the human aspects
   of network operations and the high risk of network problems caused by
   human errors.  Automation may entail the incorporation of automatic
   feedback and intelligence into some components of the traffic
   engineering system.

   Scalability: Contemporary public networks are growing very fast with
   respect to network size and traffic volume.  Therefore, a TE system
   should be scalable to remain applicable as the network evolves.  In
   particular, a TE system should remain functional as the network
   expands with regard to the number of routers and links, and with

   respect to the traffic volume.  A TE system should have a scalable
   architecture, should not adversely impair other functions and
   processes in a network element, and should not consume too much
   network resources when collecting and distributing state information
   or when exerting control.

   Stability: Stability is a very important consideration in traffic
   engineering systems that respond to changes in the state of the
   network.  State-dependent traffic engineering methodologies typically
   mandate a tradeoff between responsiveness and stability.  It is
   strongly recommended that when tradeoffs are warranted between
   responsiveness and stability, that the tradeoff should be made in
   favor of stability (especially in public IP backbone networks).

   Flexibility: A TE system should be flexible to allow for changes in
   optimization policy.  In particular, a TE system should provide
   sufficient configuration options so that a network administrator can
   tailor the TE system to a particular environment.  It may also be
   desirable to have both online and offline TE subsystems which can be
   independently enabled and disabled.  TE systems that are used in
   multi-class networks should also have options to support class based
   performance evaluation and optimization.

   Visibility: As part of the TE system, mechanisms should exist to
   collect statistics from the network and to analyze these statistics
   to determine how well the network is functioning.  Derived statistics
   such as traffic matrices, link utilization, latency, packet loss, and
   other performance measures of interest which are determined from
   network measurements can be used as indicators of prevailing network
   conditions.  Other examples of status information which should be
   observed include existing functional routing information
   (additionally, in the context of MPLS existing LSP routes), etc.

   Simplicity: Generally, a TE system should be as simple as possible.
   More importantly, the TE system should be relatively easy to use
   (i.e., clean, convenient, and intuitive user interfaces).  Simplicity
   in user interface does not necessarily imply that the TE system will
   use naive algorithms.  When complex algorithms and internal
   structures are used, such complexities should be hidden as much as
   possible from the network administrator through the user interface.

   Interoperability: Whenever feasible, traffic engineering systems and
   their components should be developed with open standards based
   interfaces to allow interoperation with other systems and components.

   Security: Security is a critical consideration in traffic engineering
   systems.  Such traffic engineering systems typically exert control
   over certain functional aspects of the network to achieve the desired

   performance objectives.  Therefore, adequate measures must be taken
   to safeguard the integrity of the traffic engineering system.
   Adequate measures must also be taken to protect the network from
   vulnerabilities that originate from security breaches and other
   impairments within the traffic engineering system.

   The remainder of this section will focus on some of the high level
   functional recommendations for traffic engineering.

6.2 Routing Recommendations

   Routing control is a significant aspect of Internet traffic
   engineering.  Routing impacts many of the key performance measures
   associated with networks, such as throughput, delay, and utilization.
   Generally, it is very difficult to provide good service quality in a
   wide area network without effective routing control.  A desirable
   routing system is one that takes traffic characteristics and network
   constraints into account during route selection while maintaining
   stability.

   Traditional shortest path first (SPF) interior gateway protocols are
   based on shortest path algorithms and have limited control
   capabilities for traffic engineering [RFC-2702, AWD2].  These
   limitations include :

   1. The well known issues with pure SPF protocols, which do not take
      network constraints and traffic characteristics into account
      during route selection.  For example, since IGPs always use the
      shortest paths (based on administratively assigned link metrics)
      to forward traffic, load sharing cannot be accomplished among
      paths of different costs.  Using shortest paths to forward traffic
      conserves network resources, but may cause the following problems:
      1) If traffic from a source to a destination exceeds the capacity
      of a link along the shortest path, the link (hence the shortest
      path) becomes congested while a longer path between these two
      nodes may be under-utilized; 2) the shortest paths from different
      sources can overlap at some links.  If the total traffic from the
      sources exceeds the capacity of any of these links, congestion
      will occur.  Problems can also occur because traffic demand
      changes over time but network topology and routing configuration
      cannot be changed as rapidly.  This causes the network topology
      and routing configuration to become sub-optimal over time, which
      may result in persistent congestion problems.

   2. The Equal-Cost Multi-Path (ECMP) capability of SPF IGPs supports
      sharing of traffic among equal cost paths between two nodes.
      However, ECMP attempts to divide the traffic as equally as
      possible among the equal cost shortest paths.  Generally, ECMP

      does not support configurable load sharing ratios among equal cost
      paths.  The result is that one of the paths may carry
      significantly more traffic than other paths because it may also
      carry traffic from other sources.  This situation can result in
      congestion along the path that carries more traffic.

   3. Modifying IGP metrics to control traffic routing tends to have
      network-wide effect.  Consequently, undesirable and unanticipated
      traffic shifts can be triggered as a result.  Recent work
      described in Section 8.0 may be capable of better control [FT00,
      FT01].

   Because of these limitations, new capabilities are needed to enhance
   the routing function in IP networks.  Some of these capabilities have
   been described elsewhere and are summarized below.

   Constraint-based routing is desirable to evolve the routing
   architecture of IP networks, especially public IP backbones with
   complex topologies [RFC-2702].  Constraint-based routing computes
   routes to fulfill requirements subject to constraints.  Constraints
   may include bandwidth, hop count, delay, and administrative policy
   instruments such as resource class attributes [RFC-2702, RFC-2386].
   This makes it possible to select routes that satisfy a given set of
   requirements subject to network and administrative policy
   constraints.  Routes computed through constraint-based routing are
   not necessarily the shortest paths.  Constraint-based routing works
   best with path oriented technologies that support explicit routing,
   such as MPLS.

   Constraint-based routing can also be used as a way to redistribute
   traffic onto the infrastructure (even for best effort traffic).  For
   example, if the bandwidth requirements for path selection and
   reservable bandwidth attributes of network links are appropriately
   defined and configured, then congestion problems caused by uneven
   traffic distribution may be avoided or reduced.  In this way, the
   performance and efficiency of the network can be improved.

   A number of enhancements are needed to conventional link state IGPs,
   such as OSPF and IS-IS, to allow them to distribute additional state
   information required for constraint-based routing.  These extensions
   to OSPF were described in [KATZ] and to IS-IS in [SMIT].
   Essentially, these enhancements require the propagation of additional
   information in link state advertisements.  Specifically, in addition
   to normal link-state information, an enhanced IGP is required to
   propagate topology state information needed for constraint-based
   routing.  Some of the additional topology state information include
   link attributes such as reservable bandwidth and link resource class
   attribute (an administratively specified property of the link).  The

   resource class attribute concept was defined in [RFC-2702].  The
   additional topology state information is carried in new TLVs and
   sub-TLVs in IS-IS, or in the Opaque LSA in OSPF [SMIT, KATZ].

   An enhanced link-state IGP may flood information more frequently than
   a normal IGP.  This is because even without changes in topology,
   changes in reservable bandwidth or link affinity can trigger the
   enhanced IGP to initiate flooding.  A tradeoff is typically required
   between the timeliness of the information flooded and the flooding
   frequency to avoid excessive consumption of link bandwidth and
   computational resources, and more importantly, to avoid instability.

   In a TE system, it is also desirable for the routing subsystem to
   make the load splitting ratio among multiple paths (with equal cost
   or different cost) configurable.  This capability gives network
   administrators more flexibility in the control of traffic
   distribution across the network.  It can be very useful for
   avoiding/relieving congestion in certain situations.  Examples can be
   found in [XIAO].

   The routing system should also have the capability to control the
   routes of subsets of traffic without affecting the routes of other
   traffic if sufficient resources exist for this purpose.  This
   capability allows a more refined control over the distribution of
   traffic across the network.  For example, the ability to move traffic
   from a source to a destination away from its original path to another
   path (without affecting other traffic paths) allows traffic to be
   moved from resource-poor network segments to resource-rich segments.
   Path oriented technologies such as MPLS inherently support this
   capability as discussed in [AWD2].

   Additionally, the routing subsystem should be able to select
   different paths for different classes of traffic (or for different
   traffic behavior aggregates) if the network supports multiple classes
   of service (different behavior aggregates).

6.3 Traffic Mapping Recommendations

   Traffic mapping pertains to the assignment of traffic workload onto
   pre-established paths to meet certain requirements.  Thus, while
   constraint-based routing deals with path selection, traffic mapping
   deals with the assignment of traffic to established paths which may
   have been selected by constraint-based routing or by some other
   means.  Traffic mapping can be performed by time-dependent or state-
   dependent mechanisms, as described in Section 5.1.

   An important aspect of the traffic mapping function is the ability to
   establish multiple paths between an originating node and a
   destination node, and the capability to distribute the traffic
   between the two nodes across the paths according to some policies.  A
   pre-condition for this scheme is the existence of flexible mechanisms
   to partition traffic and then assign the traffic partitions onto the
   parallel paths.  This requirement was noted in [RFC-2702].  When
   traffic is assigned to multiple parallel paths, it is recommended
   that special care should be taken to ensure proper ordering of
   packets belonging to the same application (or micro-flow) at the
   destination node of the parallel paths.

   As a general rule, mechanisms that perform the traffic mapping
   functions should aim to map the traffic onto the network
   infrastructure to minimize congestion.  If the total traffic load
   cannot be accommodated, or if the routing and mapping functions
   cannot react fast enough to changing traffic conditions, then a
   traffic mapping system may rely on short time scale congestion
   control mechanisms (such as queue management, scheduling, etc.) to
   mitigate congestion.  Thus, mechanisms that perform the traffic
   mapping functions should complement existing congestion control
   mechanisms.  In an operational network, it is generally desirable to
   map the traffic onto the infrastructure such that intra-class and
   inter-class resource contention are minimized.

   When traffic mapping techniques that depend on dynamic state feedback
   (e.g., MATE and such like) are used, special care must be taken to
   guarantee network stability.

6.4 Measurement Recommendations

   The importance of measurement in traffic engineering has been
   discussed throughout this document.  Mechanisms should be provided to
   measure and collect statistics from the network to support the
   traffic engineering function.  Additional capabilities may be needed
   to help in the analysis of the statistics.  The actions of these
   mechanisms should not adversely affect the accuracy and integrity of
   the statistics collected.  The mechanisms for statistical data
   acquisition should also be able to scale as the network evolves.

   Traffic statistics may be classified according to long-term or
   short-term time scales.  Long-term time scale traffic statistics are
   very useful for traffic engineering.  Long-term time scale traffic
   statistics may capture or reflect periodicity in network workload
   (such as hourly, daily, and weekly variations in traffic profiles) as
   well as traffic trends.  Aspects of the monitored traffic statistics
   may also depict class of service characteristics for a network
   supporting multiple classes of service.  Analysis of the long-term

   traffic statistics MAY yield secondary statistics such as busy hour
   characteristics, traffic growth patterns, persistent congestion
   problems, hot-spot, and imbalances in link utilization caused by
   routing anomalies.

   A mechanism for constructing traffic matrices for both long-term and
   short-term traffic statistics should be in place.  In multi-service
   IP networks, the traffic matrices may be constructed for different
   service classes.  Each element of a traffic matrix represents a
   statistic of traffic flow between a pair of abstract nodes.  An
   abstract node may represent a router, a collection of routers, or a
   site in a VPN.

   Measured traffic statistics should provide reasonable and reliable
   indicators of the current state of the network on the short-term
   scale.  Some short term traffic statistics may reflect link
   utilization and link congestion status.  Examples of congestion
   indicators include excessive packet delay, packet loss, and high
   resource utilization.  Examples of mechanisms for distributing this
   kind of information include SNMP, probing techniques, FTP, IGP link
   state advertisements, etc.

6.5 Network Survivability

   Network survivability refers to the capability of a network to
   maintain service continuity in the presence of faults.  This can be
   accomplished by promptly recovering from network impairments and
   maintaining the required QoS for existing services after recovery.
   Survivability has become an issue of great concern within the
   Internet community due to the increasing demands to carry mission
   critical traffic, real-time traffic, and other high priority traffic
   over the Internet.  Survivability can be addressed at the device
   level by developing network elements that are more reliable; and at
   the network level by incorporating redundancy into the architecture,
   design, and operation of networks.  It is recommended that a
   philosophy of robustness and survivability should be adopted in the
   architecture, design, and operation of traffic engineering that
   control IP networks (especially public IP networks).  Because
   different contexts may demand different levels of survivability, the
   mechanisms developed to support network survivability should be
   flexible so that they can be tailored to different needs.

   Failure protection and restoration capabilities have become available
   from multiple layers as network technologies have continued to
   improve.  At the bottom of the layered stack, optical networks are
   now capable of providing dynamic ring and mesh restoration
   functionality at the wavelength level as well as traditional
   protection functionality.  At the SONET/SDH layer survivability

   capability is provided with Automatic Protection Switching (APS) as
   well as self-healing ring and mesh architectures.  Similar
   functionality is provided by layer 2 technologies such as ATM
   (generally with slower mean restoration times).  Rerouting is
   traditionally used at the IP layer to restore service following link
   and node outages.  Rerouting at the IP layer occurs after a period of
   routing convergence which may require seconds to minutes to complete.
   Some new developments in the MPLS context make it possible to achieve
   recovery at the IP layer prior to convergence [SHAR].

   To support advanced survivability requirements, path-oriented
   technologies such a MPLS can be used to enhance the survivability of
   IP networks in a potentially cost effective manner.  The advantages
   of path oriented technologies such as MPLS for IP restoration becomes
   even more evident when class based protection and restoration
   capabilities are required.

   Recently, a common suite of control plane protocols has been proposed
   for both MPLS and optical transport networks under the acronym
   Multi-protocol Lambda Switching [AWD1].  This new paradigm of Multi-
   protocol Lambda Switching will support even more sophisticated mesh
   restoration capabilities at the optical layer for the emerging IP
   over WDM network architectures.

   Another important aspect regarding multi-layer survivability is that
   technologies at different layers provide protection and restoration
   capabilities at different temporal granularities (in terms of time
   scales) and at different bandwidth granularity (from packet-level to
   wavelength level).  Protection and restoration capabilities can also
   be sensitive to different service classes and different network
   utility models.

   The impact of service outages varies significantly for different
   service classes depending upon the effective duration of the outage.
   The duration of an outage can vary from milliseconds (with minor
   service impact) to seconds (with possible call drops for IP telephony
   and session time-outs for connection oriented transactions) to
   minutes and hours (with potentially considerable social and business
   impact).

   Coordinating different protection and restoration capabilities across
   multiple layers in a cohesive manner to ensure network survivability
   is maintained at reasonable cost is a challenging task.  Protection
   and restoration coordination across layers may not always be
   feasible, because networks at different layers may belong to
   different administrative domains.

   The following paragraphs present some of the general recommendations
   for protection and restoration coordination.

   -  Protection and restoration capabilities from different layers
   should be coordinated whenever feasible and appropriate to provide
   network survivability in a flexible and cost effective manner.
   Minimization of function duplication across layers is one way to
   achieve the coordination.  Escalation of alarms and other fault
   indicators from lower to higher layers may also be performed in a
   coordinated manner.  A temporal order of restoration trigger timing
   at different layers is another way to coordinate multi-layer
   protection/restoration.

   -  Spare capacity at higher layers is often regarded as working
   traffic at lower layers.  Placing protection/restoration functions in
   many layers may increase redundancy and robustness, but it should not
   result in significant and avoidable inefficiencies in network
   resource utilization.

   -  It is generally desirable to have protection and restoration
   schemes that are bandwidth efficient.

   -  Failure notification throughout the network should be timely and
   reliable.

   -  Alarms and other fault monitoring and reporting capabilities
   should be provided at appropriate layers.

6.5.1 Survivability in MPLS Based Networks

   MPLS is an important emerging technology that enhances IP networks in
   terms of features, capabilities, and services.  Because MPLS is
   path-oriented, it can potentially provide faster and more predictable
   protection and restoration capabilities than conventional hop by hop
   routed IP systems.  This subsection describes some of the basic
   aspects and recommendations for MPLS networks regarding protection
   and restoration.  See [SHAR] for a more comprehensive discussion on
   MPLS based recovery.

   Protection types for MPLS networks can be categorized as link
   protection, node protection, path protection, and segment protection.

   -  Link Protection: The objective for link protection is to protect
      an LSP from a given link failure.  Under link protection, the path
      of the protection or backup LSP (the secondary LSP) is disjoint
      from the path of the working or operational LSP at the particular
      link over which protection is required.  When the protected link
      fails, traffic on the working LSP is switched over to the

      protection LSP at the head-end of the failed link.  This is a
      local repair method which can be fast.  It might be more
      appropriate in situations where some network elements along a
      given path are less reliable than others.

   -  Node Protection: The objective of LSP node protection is to
      protect an LSP from a given node failure.  Under node protection,
      the path of the protection LSP is disjoint from the path of the
      working LSP at the particular node to be protected.  The secondary
      path is also disjoint from the primary path at all links
      associated with the node to be protected.  When the node fails,
      traffic on the working LSP is switched over to the protection LSP
      at the upstream LSR directly connected to the failed node.

   -  Path Protection: The goal of LSP path protection is to protect an
      LSP from failure at any point along its routed path.  Under path
      protection, the path of the protection LSP is completely disjoint
      from the path of the working LSP.  The advantage of path
      protection is that the backup LSP protects the working LSP from
      all possible link and node failures along the path, except for
      failures that might occur at the ingress and egress LSRs, or for
      correlated failures that might impact both working and backup
      paths simultaneously.  Additionally, since the path selection is
      end-to-end, path protection might be more efficient in terms of
      resource usage than link or node protection.  However, path
      protection may be slower than link and node protection in general.

   -  Segment Protection: An MPLS domain may be partitioned into
      multiple protection domains whereby a failure in a protection
      domain is rectified within that domain.  In cases where an LSP
      traverses multiple protection domains, a protection mechanism
      within a domain only needs to protect the segment of the LSP that
      lies within the domain.  Segment protection will generally be
      faster than path protection because recovery generally occurs
      closer to the fault.

6.5.2 Protection Option

   Another issue to consider is the concept of protection options.  The
   protection option uses the notation m:n protection, where m is the
   number of protection LSPs used to protect n working LSPs.  Feasible
   protection options follow.

   -  1:1: one working LSP is protected/restored by one protection LSP.

   -  1:n: one protection LSP is used to protect/restore n working LSPs.

   -  n:1: one working LSP is protected/restored by n protection LSPs,
      possibly with configurable load splitting ratio.  When more than
      one protection LSP is used, it may be desirable to share the
      traffic across the protection LSPs when the working LSP fails to
      satisfy the bandwidth requirement of the traffic trunk associated
      with the working LSP.  This may be especially useful when it is
      not feasible to find one path that can satisfy the bandwidth
      requirement of the primary LSP.

   -  1+1: traffic is sent concurrently on both the working LSP and the
      protection LSP.  In this case, the egress LSR selects one of the
      two LSPs based on a local traffic integrity decision process,
      which compares the traffic received from both the working and the
      protection LSP and identifies discrepancies.  It is unlikely that
      this option would be used extensively in IP networks due to its
      resource utilization inefficiency.  However, if bandwidth becomes
      plentiful and cheap, then this option might become quite viable
      and attractive in IP networks.

6.6 Traffic Engineering in Diffserv Environments

   This section provides an overview of the traffic engineering features
   and recommendations that are specifically pertinent to Differentiated
   Services (Diffserv) [RFC-2475] capable IP networks.

   Increasing requirements to support multiple classes of traffic, such
   as best effort and mission critical data, in the Internet calls for
   IP networks to differentiate traffic according to some criteria, and
   to accord preferential treatment to certain types of traffic.  Large
   numbers of flows can be aggregated into a few behavior aggregates
   based on some criteria in terms of common performance requirements in
   terms of packet loss ratio, delay, and jitter; or in terms of common
   fields within the IP packet headers.

   As Diffserv evolves and becomes deployed in operational networks,
   traffic engineering will be critical to ensuring that SLAs defined
   within a given Diffserv service model are met.  Classes of service
   (CoS) can be supported in a Diffserv environment by concatenating
   per-hop behaviors (PHBs) along the routing path, using service
   provisioning mechanisms, and by appropriately configuring edge
   functionality such as traffic classification, marking, policing, and
   shaping.  PHB is the forwarding behavior that a packet receives at a
   DS node (a Diffserv-compliant node).  This is accomplished by means
   of buffer management and packet scheduling mechanisms.  In this
   context, packets belonging to a class are those that are members of a
   corresponding ordering aggregate.

   Traffic engineering can be used as a compliment to Diffserv
   mechanisms to improve utilization of network resources, but not as a
   necessary element in general.  When traffic engineering is used, it
   can be operated on an aggregated basis across all service classes
   [RFC-3270] or on a per service class basis.  The former is used to
   provide better distribution of the aggregate traffic load over the
   network resources.  (See [RFC-3270] for detailed mechanisms to
   support aggregate traffic engineering.)  The latter case is discussed
   below since it is specific to the Diffserv environment, with so
   called Diffserv-aware traffic engineering [DIFF_TE].

   For some Diffserv networks, it may be desirable to control the
   performance of some service classes by enforcing certain
   relationships between the traffic workload contributed by each
   service class and the amount of network resources allocated or
   provisioned for that service class.  Such relationships between
   demand and resource allocation can be enforced using a combination
   of, for example: (1) traffic engineering mechanisms on a per service
   class basis that enforce the desired relationship between the amount
   of traffic contributed by a given service class and the resources
   allocated to that class, and (2) mechanisms that dynamically adjust
   the resources allocated to a given service class to relate to the
   amount of traffic contributed by that service class.

   It may also be desirable to limit the performance impact of high
   priority traffic on relatively low priority traffic.  This can be
   achieved by, for example, controlling the percentage of high priority
   traffic that is routed through a given link.  Another way to
   accomplish this is to increase link capacities appropriately so that
   lower priority traffic can still enjoy adequate service quality.
   When the ratio of traffic workload contributed by different service
   classes vary significantly from router to router, it may not suffice
   to rely exclusively on conventional IGP routing protocols or on
   traffic engineering mechanisms that are insensitive to different
   service classes.  Instead, it may be desirable to perform traffic
   engineering, especially routing control and mapping functions, on a
   per service class basis.  One way to accomplish this in a domain that
   supports both MPLS and Diffserv is to define class specific LSPs and
   to map traffic from each class onto one or more LSPs that correspond
   to that service class.  An LSP corresponding to a given service class
   can then be routed and protected/restored in a class dependent
   manner, according to specific policies.

   Performing traffic engineering on a per class basis may require
   certain per-class parameters to be distributed.  Note that it is
   common to have some classes share some aggregate constraint (e.g.,
   maximum bandwidth requirement) without enforcing the constraint on
   each individual class.  These classes then can be grouped into a

   class-type and per-class-type parameters can be distributed instead
   to improve scalability.  It also allows better bandwidth sharing
   between classes in the same class-type.  A class-type is a set of
   classes that satisfy the following two conditions:

   1) Classes in the same class-type have common aggregate requirements
   to satisfy required performance levels.

   2) There is no requirement to be enforced at the level of individual
   class in the class-type.  Note that it is still possible,
   nevertheless, to implement some priority policies for classes in the
   same class-type to permit preferential access to the class-type
   bandwidth through the use of preemption priorities.

   An example of the class-type can be a low-loss class-type that
   includes both AF1-based and AF2-based Ordering Aggregates.  With such
   a class-type, one may implement some priority policy which assigns
   higher preemption priority to AF1-based traffic trunks over AF2-based
   ones, vice versa, or the same priority.

   See [DIFF-TE] for detailed requirements on Diffserv-aware traffic
   engineering.

6.7 Network Controllability

   Off-line (and on-line) traffic engineering considerations would be of
   limited utility if the network could not be controlled effectively to
   implement the results of TE decisions and to achieve desired network
   performance objectives.  Capacity augmentation is a coarse grained
   solution to traffic engineering issues.  However, it is simple and
   may be advantageous if bandwidth is abundant and cheap or if the
   current or expected network workload demands it.  However, bandwidth
   is not always abundant and cheap, and the workload may not always
   demand additional capacity.  Adjustments of administrative weights
   and other parameters associated with routing protocols provide finer
   grained control, but is difficult to use and imprecise because of the
   routing interactions that occur across the network.  In certain
   network contexts, more flexible, finer grained approaches which
   provide more precise control over the mapping of traffic to routes
   and over the selection and placement of routes may be appropriate and
   useful.

   Control mechanisms can be manual (e.g., administrative
   configuration), partially-automated (e.g., scripts) or fully-
   automated (e.g., policy based management systems).  Automated
   mechanisms are particularly required in large scale networks.
   Multi-vendor interoperability can be facilitated by developing and
   deploying standardized management

   systems (e.g., standard MIBs) and policies (PIBs) to support the
   control functions required to address traffic engineering objectives
   such as load distribution and protection/restoration.

   Network control functions should be secure, reliable, and stable as
   these are often needed to operate correctly in times of network
   impairments (e.g., during network congestion or security attacks).

7.0 Inter-Domain Considerations

   Inter-domain traffic engineering is concerned with the performance
   optimization for traffic that originates in one administrative domain
   and terminates in a different one.

   Traffic exchange between autonomous systems in the Internet occurs
   through exterior gateway protocols.  Currently, BGP [BGP4] is the
   standard exterior gateway protocol for the Internet.  BGP provides a
   number of attributes and capabilities (e.g., route filtering) that
   can be used for inter-domain traffic engineering.  More specifically,
   BGP permits the control of routing information and traffic exchange
   between Autonomous Systems (AS's) in the Internet.  BGP incorporates
   a sequential decision process which calculates the degree of
   preference for various routes to a given destination network.  There
   are two fundamental aspects to inter-domain traffic engineering using
   BGP:

   -  Route Redistribution: controlling the import and export of routes
      between AS's, and controlling the redistribution of routes between
      BGP and other protocols within an AS.

   -  Best path selection: selecting the best path when there are
      multiple candidate paths to a given destination network.  Best
      path selection is performed by the BGP decision process based on a
      sequential procedure, taking a number of different considerations
      into account.  Ultimately, best path selection under BGP boils
      down to selecting preferred exit points out of an AS towards
      specific destination networks.  The BGP path selection process can
      be influenced by manipulating the attributes associated with the
      BGP decision process.  These attributes include: NEXT-HOP, WEIGHT
      (Cisco proprietary which is also implemented by some other
      vendors), LOCAL-PREFERENCE, AS-PATH, ROUTE-ORIGIN, MULTI-EXIT-
      DESCRIMINATOR (MED), IGP METRIC, etc.

   Route-maps provide the flexibility to implement complex BGP policies
   based on pre-configured logical conditions.  In particular, Route-
   maps can be used to control import and export policies for incoming
   and outgoing routes, control the redistribution of routes between BGP
   and other protocols, and influence the selection of best paths by

   manipulating the attributes associated with the BGP decision process.
   Very complex logical expressions that implement various types of
   policies can be implemented using a combination of Route-maps, BGP-
   attributes, Access-lists, and Community attributes.

   When looking at possible strategies for inter-domain TE with BGP, it
   must be noted that the outbound traffic exit point is controllable,
   whereas the interconnection point where inbound traffic is received
   from an EBGP peer typically is not, unless a special arrangement is
   made with the peer sending the traffic.  Therefore, it is up to each
   individual network to implement sound TE strategies that deal with
   the efficient delivery of outbound traffic from one's customers to
   one's peering points.  The vast majority of TE policy is based upon a
   "closest exit" strategy, which offloads interdomain traffic at the
   nearest outbound peer point towards the destination autonomous
   system.  Most methods of manipulating the point at which inbound
   traffic enters a network from an EBGP peer (inconsistent route
   announcements between peering points, AS pre-pending, and sending
   MEDs) are either ineffective, or not accepted in the peering
   community.

   Inter-domain TE with BGP is generally effective, but it is usually
   applied in a trial-and-error fashion.  A systematic approach for
   inter-domain traffic engineering is yet to be devised.

   Inter-domain TE is inherently more difficult than intra-domain TE
   under the current Internet architecture.  The reasons for this are
   both technical and administrative.  Technically, while topology and
   link state information are helpful for mapping traffic more
   effectively, BGP does not propagate such information across domain
   boundaries for stability and scalability reasons.  Administratively,
   there are differences in operating costs and network capacities
   between domains.  Generally, what may be considered a good solution
   in one domain may not necessarily be a good solution in another
   domain.  Moreover, it would generally be considered inadvisable for
   one domain to permit another domain to influence the routing and
   management of traffic in its network.

   MPLS TE-tunnels (explicit LSPs) can potentially add a degree of
   flexibility in the selection of exit points for inter-domain routing.
   The concept of relative and absolute metrics can be applied to this
   purpose.  The idea is that if BGP attributes are defined such that
   the BGP decision process depends on IGP metrics to select exit points
   for inter-domain traffic, then some inter-domain traffic destined to
   a given peer network can be made to prefer a specific exit point by
   establishing a TE-tunnel between the router making the selection to
   the peering point via a TE-tunnel and assigning the TE-tunnel a
   metric which is smaller than the IGP cost to all other peering

   points.  If a peer accepts and processes MEDs, then a similar MPLS
   TE-tunnel based scheme can be applied to cause certain entrance
   points to be preferred by setting MED to be an IGP cost, which has
   been modified by the tunnel metric.

   Similar to intra-domain TE, inter-domain TE is best accomplished when
   a traffic matrix can be derived to depict the volume of traffic from
   one autonomous system to another.

   Generally, redistribution of inter-domain traffic requires
   coordination between peering partners.  An export policy in one
   domain that results in load redistribution across peer points with
   another domain can significantly affect the local traffic matrix
   inside the domain of the peering partner.  This, in turn, will affect
   the intra-domain TE due to changes in the spatial distribution of
   traffic.  Therefore, it is mutually beneficial for peering partners
   to coordinate with each other before attempting any policy changes
   that may result in significant shifts in inter-domain traffic.  In
   certain contexts, this coordination can be quite challenging due to
   technical and non- technical reasons.

   It is a matter of speculation as to whether MPLS, or similar
   technologies, can be extended to allow selection of constrained paths
   across domain boundaries.

8.0 Overview of Contemporary TE Practices in Operational IP Networks

   This section provides an overview of some contemporary traffic
   engineering practices in IP networks.  The focus is primarily on the
   aspects that pertain to the control of the routing function in
   operational contexts.  The intent here is to provide an overview of
   the commonly used practices.  The discussion is not intended to be
   exhaustive.

   Currently, service providers apply many of the traffic engineering
   mechanisms discussed in this document to optimize the performance of
   their IP networks.  These techniques include capacity planning for
   long time scales, routing control using IGP metrics and MPLS for
   medium time scales, the overlay model also for medium time scales,
   and traffic management mechanisms for short time scale.

   When a service provider plans to build an IP network, or expand the
   capacity of an existing network, effective capacity planning should
   be an important component of the process.  Such plans may take the
   following aspects into account: location of new nodes if any,
   existing and predicted traffic patterns, costs, link capacity,
   topology, routing design, and survivability.

   Performance optimization of operational networks is usually an
   ongoing process in which traffic statistics, performance parameters,
   and fault indicators are continually collected from the network.
   This empirical data is then analyzed and used to trigger various
   traffic engineering mechanisms.  Tools that perform what-if analysis
   can also be used to assist the TE process by allowing various
   scenarios to be reviewed before a new set of configurations are
   implemented in the operational network.

   Traditionally, intra-domain real-time TE with IGP is done by
   increasing the OSPF or IS-IS metric of a congested link until enough
   traffic has been diverted from that link.  This approach has some
   limitations as discussed in Section 6.2.  Recently, some new intra-
   domain TE approaches/tools have been proposed
   [RR94][FT00][FT01][WANG].  Such approaches/tools take traffic matrix,
   network topology, and network performance objective(s) as input, and
   produce some link metrics and possibly some unequal load-sharing
   ratios to be set at the head-end routers of some ECMPs as output.
   These new progresses open new possibility for intra-domain TE with
   IGP to be done in a more systematic way.

   The overlay model (IP over ATM or IP over Frame relay) is another
   approach which is commonly used in practice [AWD2].  The IP over ATM
   technique is no longer viewed favorably due to recent advances in
   MPLS and router hardware technology.

   Deployment of MPLS for traffic engineering applications has commenced
   in some service provider networks.  One operational scenario is to
   deploy MPLS in conjunction with an IGP (IS-IS-TE or OSPF-TE) that
   supports the traffic engineering extensions, in conjunction with
   constraint-based routing for explicit route computations, and a
   signaling protocol (e.g., RSVP-TE or CRLDP) for LSP instantiation.

   In contemporary MPLS traffic engineering contexts, network
   administrators specify and configure link attributes and resource
   constraints such as maximum reservable bandwidth and resource class
   attributes for links (interfaces) within the MPLS domain.  A link
   state protocol that supports TE extensions (IS-IS-TE or OSPF-TE) is
   used to propagate information about network topology and link
   attribute to all routers in the routing area.  Network administrators
   also specify all the LSPs that are to originate each router.  For
   each LSP, the network administrator specifies the destination node
   and the attributes of the LSP which indicate the requirements that to
   be satisfied during the path selection process.  Each router then
   uses a local constraint-based routing process to compute explicit
   paths for all LSPs originating from it.  Subsequently, a signaling

   protocol is used to instantiate the LSPs.  By assigning proper
   bandwidth values to links and LSPs, congestion caused by uneven
   traffic distribution can generally be avoided or mitigated.

   The bandwidth attributes of LSPs used for traffic engineering can be
   updated periodically.  The basic concept is that the bandwidth
   assigned to an LSP should relate in some manner to the bandwidth
   requirements of traffic that actually flows through the LSP.  The
   traffic attribute of an LSP can be modified to accommodate traffic
   growth and persistent traffic shifts.  If network congestion occurs
   due to some unexpected events, existing LSPs can be rerouted to
   alleviate the situation or network administrator can configure new
   LSPs to divert some traffic to alternative paths.  The reservable
   bandwidth of the congested links can also be reduced to force some
   LSPs to be rerouted to other paths.

   In an MPLS domain, a traffic matrix can also be estimated by
   monitoring the traffic on LSPs.  Such traffic statistics can be used
   for a variety of purposes including network planning and network
   optimization.  Current practice suggests that deploying an MPLS
   network consisting of hundreds of routers and thousands of LSPs is
   feasible.  In summary, recent deployment experience suggests that
   MPLS approach is very effective for traffic engineering in IP
   networks [XIAO].

   As mentioned previously in Section 7.0, one usually has no direct
   control over the distribution of inbound traffic.  Therefore, the
   main goal of contemporary inter-domain TE is to optimize the
   distribution of outbound traffic between multiple inter-domain links.
   When operating a global network, maintaining the ability to operate
   the network in a regional fashion where desired, while continuing to
   take advantage of the benefits of a global network, also becomes an
   important objective.

   Inter-domain TE with BGP usually begins with the placement of
   multiple peering interconnection points in locations that have high
   peer density, are in close proximity to originating/terminating
   traffic locations on one's own network, and are lowest in cost.
   There are generally several locations in each region of the world
   where the vast majority of major networks congregate and
   interconnect.  Some location-decision problems that arise in
   association with inter-domain routing are discussed in [AWD5].

   Once the locations of the interconnects are determined, and circuits
   are implemented, one decides how best to handle the routes heard from
   the peer, as well as how to propagate the peers' routes within one's
   own network.  One way to engineer outbound traffic flows on a network
   with many EBGP peers is to create a hierarchy of peers.  Generally,

   the Local Preferences of all peers are set to the same value so that
   the shortest AS paths will be chosen to forward traffic.  Then, by
   over-writing the inbound MED metric (Multi-exit-discriminator metric,
   also referred to as "BGP metric".  Both terms are used
   interchangeably in this document) with BGP metrics to routes received
   at different peers, the hierarchy can be formed.  For example, all
   Local Preferences can be set to 200, preferred private peers can be
   assigned a BGP metric of 50, the rest of the private peers can be
   assigned a BGP metric of 100, and public peers can be assigned a BGP
   metric of 600.  "Preferred" peers might be defined as those peers
   with whom the most available capacity exists, whose customer base is
   larger in comparison to other peers, whose interconnection costs are
   the lowest, and with whom upgrading existing capacity is the easiest.
   In a network with low utilization at the edge, this works well.  The
   same concept could be applied to a network with higher edge
   utilization by creating more levels of BGP metrics between peers,
   allowing for more granularity in selecting the exit points for
   traffic bound for a dual homed customer on a peer's network.

   By only replacing inbound MED metrics with BGP metrics, only equal
   AS-Path length routes' exit points are being changed.  (The BGP
   decision considers Local Preference first, then AS-Path length, and
   then BGP metric).  For example, assume a network has two possible
   egress points, peer A and peer B.  Each peer has 40% of the
   Internet's routes exclusively on its network, while the remaining 20%
   of the Internet's routes are from customers who dual home between A
   and B.  Assume that both peers have a Local Preference of 200 and a
   BGP metric of 100.  If the link to peer A is congested, increasing
   its BGP metric while leaving the Local Preference at 200 will ensure
   that the 20% of total routes belonging to dual homed customers will
   prefer peer B as the exit point.  The previous example would be used
   in a situation where all exit points to a given peer were close to
   congestion levels, and traffic needed to be shifted away from that
   peer entirely.

   When there are multiple exit points to a given peer, and only one of
   them is congested, it is not necessary to shift traffic away from the
   peer entirely, but only from the one congested circuit.  This can be
   achieved by using passive IGP-metrics, AS-path filtering, or prefix
   filtering.

   Occasionally, more drastic changes are needed, for example, in
   dealing with a "problem peer" who is difficult to work with on
   upgrades or is charging high prices for connectivity to their
   network.  In that case, the Local Preference to that peer can be
   reduced below the level of other peers.  This effectively reduces the
   amount of traffic sent to that peer to only originating traffic

   (assuming no transit providers are involved).  This type of change
   can affect a large amount of traffic, and is only used after other
   methods have failed to provide the desired results.

   Although it is not much of an issue in regional networks, the
   propagation of a peer's routes back through the network must be
   considered when a network is peering on a global scale.  Sometimes,
   business considerations can influence the choice of BGP policies in a
   given context.  For example, it may be imprudent, from a business
   perspective, to operate a global network and provide full access to
   the global customer base to a small network in a particular country.
   However, for the purpose of providing one's own customers with
   quality service in a particular region, good connectivity to that
   in-country network may still be necessary.  This can be achieved by
   assigning a set of communities at the edge of the network, which have
   a known behavior when routes tagged with those communities are
   propagating back through the core.  Routes heard from local peers
   will be prevented from propagating back to the global network,
   whereas routes learned from larger peers may be allowed to propagate
   freely throughout the entire global network.  By implementing a
   flexible community strategy, the benefits of using a single global AS
   Number (ASN) can be realized, while the benefits of operating
   regional networks can also be taken advantage of.  An alternative to
   doing this is to use different ASNs in different regions, with the
   consequence that the AS path length for routes announced by that
   service provider will increase.

9.0 Conclusion

   This document described principles for traffic engineering in the
   Internet.  It presented an overview of some of the basic issues
   surrounding traffic engineering in IP networks.  The context of TE
   was described, a TE process models and a taxonomy of TE styles were
   presented.  A brief historical review of pertinent developments
   related to traffic engineering was provided.  A survey of
   contemporary TE techniques in operational networks was presented.
   Additionally, the document specified a set of generic requirements,
   recommendations, and options for Internet traffic engineering.

10.0 Security Considerations

This document does not introduce new security issues.

11.0 Acknowledgments

   The authors would like to thank Jim Boyle for inputs on the
   recommendations section, Francois Le Faucheur for inputs on Diffserv
   aspects, Blaine Christian for inputs on measurement, Gerald Ash for

   inputs on routing in telephone networks and for text on event-
   dependent TE methods, Steven Wright for inputs on network
   controllability, and Jonathan Aufderheide for inputs on inter-domain
   TE with BGP.  Special thanks to Randy Bush for proposing the TE
   taxonomy based on "tactical vs strategic" methods.  The subsection
   describing an "Overview of ITU Activities Related to Traffic
   Engineering" was adapted from a contribution by Waisum Lai.  Useful
   feedback and pointers to relevant materials were provided by J. Noel
   Chiappa.  Additional comments were provided by Glenn Grotefeld during
   the working last call process.  Finally, the authors would like to
   thank Ed Kern, the TEWG co-chair, for his comments and support.

12.0 References

   [ASH2]      J. Ash, Dynamic Routing in Telecommunications Networks,
               McGraw Hill, 1998.

   [ASH3]      Ash, J., "TE & QoS Methods for IP-, ATM-, & TDM-Based
               Networks", Work in Progress, March 2001.

   [AWD1]      D. Awduche and Y. Rekhter, "Multiprocotol Lambda
               Switching:  Combining MPLS Traffic Engineering Control
               with Optical Crossconnects", IEEE Communications
               Magazine, March 2001.

   [AWD2]      D. Awduche, "MPLS and Traffic Engineering in IP
               Networks", IEEE Communications Magazine, Dec. 1999.

   [AWD5]      D. Awduche et al, "An Approach to Optimal Peering Between
               Autonomous Systems in the Internet", International
               Conference on Computer Communications and Networks
               (ICCCN'98), Oct. 1998.

   [CRUZ]      R. L. Cruz, "A Calculus for Network Delay, Part II:
               Network Analysis", IEEE Transactions on Information
               Theory, vol. 37, pp.  132-141, 1991.

   [DIFF-TE]   Le Faucheur, F., Nadeau, T., Tatham, M., Telkamp, T.,
               Cooper, D., Boyle, J., Lai, W., Fang, L., Ash, J., Hicks,
               P., Chui, A., Townsend, W. and D. Skalecki, "Requirements
               for support of Diff-Serv-aware MPLS Traffic Engineering",
               Work in Progress, May 2001.

   [ELW95]     A. Elwalid, D. Mitra and R.H. Wentworth, "A New Approach
               for Allocating Buffers and Bandwidth to Heterogeneous,
               Regulated Traffic in an ATM Node", IEEE IEEE Journal on
               Selected Areas in Communications, 13:6, pp. 1115-1127,
               Aug. 1995.

   [FGLR]      A. Feldmann, A. Greenberg, C. Lund, N. Reingold, and J.
               Rexford, "NetScope: Traffic Engineering for IP Networks",
               IEEE Network Magazine, 2000.

   [FLJA93]    S. Floyd and V. Jacobson, "Random Early Detection
               Gateways for Congestion Avoidance", IEEE/ACM Transactions
               on Networking, Vol. 1 Nov. 4., p. 387-413, Aug. 1993.

   [FLOY94]    S. Floyd, "TCP and Explicit Congestion Notification", ACM
               Computer Communication Review, V. 24, No. 5, p. 10-23,
               Oct. 1994.

   [FT00]      B. Fortz and M. Thorup, "Internet Traffic Engineering by
               Optimizing OSPF Weights", IEEE INFOCOM 2000, Mar. 2000.

   [FT01]      B. Fortz and M. Thorup, "Optimizing OSPF/IS-IS Weights in
               a Changing World",
               www.research.att.com/~mthorup/PAPERS/papers.html.

   [HUSS87]    B.R. Hurley, C.J.R. Seidl and W.F. Sewel, "A Survey of
               Dynamic Routing Methods for Circuit-Switched Traffic",
               IEEE Communication Magazine, Sep. 1987.

   [ITU-E600]  ITU-T Recommendation E.600, "Terms and Definitions of
               Traffic Engineering", Mar. 1993.

   [ITU-E701]  ITU-T Recommendation E.701, "Reference Connections for
               Traffic Engineering", Oct. 1993.

   [ITU-E801]  ITU-T Recommendation E.801, "Framework for Service
               Quality Agreement", Oct. 1996.

   [JAM]       Jamoussi, B., Editior, Andersson, L., Collon, R. and R.
               Dantu, "Constraint-Based LSP Setup using LDP", RFC 3212,
               January 2002.

   [KATZ]      Katz, D., Yeung, D. and K. Kompella, "Traffic Engineering
               Extensions to OSPF", Work in Progress, February 2001.

   [LNO96]     T. Lakshman, A. Neidhardt, and T. Ott, "The Drop from
               Front Strategy in TCP over ATM and its Interworking with
               other Control Features", Proc. INFOCOM'96, p. 1242-1250,
               1996.

   [MA]        Q. Ma, "Quality of Service Routing in Integrated Services
               Networks", PhD Dissertation, CMU-CS-98-138, CMU, 1998.

   [MATE]      A. Elwalid, C. Jin, S. Low, and I. Widjaja, "MATE: MPLS
               Adaptive Traffic Engineering", Proc. INFOCOM'01, Apr.
               2001.

   [MCQ80]     J.M. McQuillan, I. Richer, and E.C. Rosen, "The New
               Routing Algorithm for the ARPANET", IEEE.  Trans. on
               Communications, vol. 28, no. 5, pp. 711-719, May 1980.

   [MR99]      D. Mitra and K.G. Ramakrishnan, "A Case Study of
               Multiservice, Multipriority Traffic Engineering Design
               for Data Networks", Proc. Globecom'99, Dec 1999.

   [RFC-1458]  Braudes, R. and S. Zabele, "Requirements for Multicast
               Protocols", RFC 1458, May 1993.

   [RFC-1771]  Rekhter, Y. and T. Li, "A Border Gateway Protocol 4
               (BGP-4)", RFC 1771, March 1995.

   [RFC-1812]  Baker, F., "Requirements for IP Version 4 Routers", STD
               4, RFC 1812, June 1995.

   [RFC-1992]  Castineyra, I., Chiappa, N. and M. Steenstrup, "The
               Nimrod Routing Architecture", RFC 1992, August 1996.

   [RFC-1997]  Chandra, R., Traina, P. and T. Li, "BGP Community
               Attributes", RFC 1997, August 1996.

   [RFC-1998]  Chen, E. and T. Bates, "An Application of the BGP
               Community Attribute in Multi-home Routing", RFC 1998,
               August 1996.

   [RFC-2205]  Braden, R., Zhang, L., Berson, S., Herzog, S. and S.
               Jamin, "Resource Reservation Protocol (RSVP) - Version 1
               Functional Specification", RFC 2205, September 1997.

   [RFC-2211]  Wroclawski, J., "Specification of the Controlled-Load
               Network Element Service", RFC 2211, September 1997.

   [RFC-2212]  Shenker, S., Partridge, C. and R. Guerin, "Specification
               of Guaranteed Quality of Service", RFC 2212, September
               1997.

   [RFC-2215]  Shenker, S. and J. Wroclawski, "General Characterization
               Parameters for Integrated Service Network Elements", RFC
               2215, September 1997.

   [RFC-2216]  Shenker, S. and J. Wroclawski, "Network Element Service
               Specification Template", RFC 2216, September 1997.

   [RFC-2328]  Moy, J., "OSPF Version 2", STD 54, RFC 2328, July 1997.

   [RFC-2330]  Paxson, V., Almes, G., Mahdavi, J. and M. Mathis,
               "Framework for IP Performance Metrics", RFC 2330, May
               1998.

   [RFC-2386]  Crawley, E., Nair, R., Rajagopalan, B. and H. Sandick, "A
               Framework for QoS-based Routing in the Internet", RFC
               2386, August 1998.

   [RFC-2474]  Nichols, K., Blake, S., Baker, F. and D. Black,
               "Definition of the Differentiated Services Field (DS
               Field) in the IPv4 and IPv6 Headers", RFC 2474, December
               1998.

   [RFC-2475]  Blake, S., Black, D., Carlson, M., Davies, E., Wang, Z.
               and W. Weiss, "An Architecture for Differentiated
               Services", RFC 2475, December 1998.

   [RFC-2597]  Heinanen, J., Baker, F., Weiss, W. and J. Wroclawski,
               "Assured Forwarding PHB Group", RFC 2597, June 1999.

   [RFC-2678]  Mahdavi, J. and V. Paxson, "IPPM Metrics for Measuring
               Connectivity", RFC 2678, September 1999.

   [RFC-2679]  Almes, G., Kalidindi, S. and M. Zekauskas, "A One-way
               Delay Metric for IPPM", RFC 2679, September 1999.

   [RFC-2680]  Almes, G., Kalidindi, S. and M. Zekauskas, "A One-way
               Packet Loss Metric for IPPM", RFC 2680, September 1999.

   [RFC-2702]  Awduche, D., Malcolm, J., Agogbua, J., O'Dell, M. and J.
               McManus, "Requirements for Traffic Engineering over
               MPLS", RFC 2702, September 1999.

   [RFC-2722]  Brownlee, N., Mills, C. and G. Ruth, "Traffic Flow
               Measurement: Architecture", RFC 2722, October 1999.

   [RFC-2753]  Yavatkar, R., Pendarakis, D. and R. Guerin, "A Framework
               for Policy-based Admission Control", RFC 2753, January
               2000.

   [RFC-2961]  Berger, L., Gan, D., Swallow, G., Pan, P., Tommasi, F.
               and S. Molendini, "RSVP Refresh Overhead Reduction
               Extensions", RFC 2961, April 2000.

   [RFC-2998]  Bernet, Y., Ford, P., Yavatkar, R., Baker, F., Zhang, L.,
               Speer, M., Braden, R., Davie, B., Wroclawski, J. and E.
               Felstaine, "A Framework for Integrated Services Operation
               over Diffserv Networks", RFC 2998, November 2000.

   [RFC-3031]  Rosen, E., Viswanathan, A. and R. Callon, "Multiprotocol
               Label Switching Architecture", RFC 3031, January 2001.

   [RFC-3086]  Nichols, K. and B. Carpenter, "Definition of
               Differentiated Services Per Domain Behaviors and Rules
               for their Specification", RFC 3086, April 2001.

   [RFC-3124]  Balakrishnan, H. and S. Seshan, "The Congestion Manager",
               RFC 3124, June 2001.

   [RFC-3209]  Awduche, D., Berger, L., Gan, D., Li, T., Srinivasan, V.
               and G. Swallow, "RSVP-TE: Extensions to RSVP for LSP
               Tunnels", RFC 3209, December 2001.

   [RFC-3210]  Awduche, D., Hannan, A. and X. Xiao, "Applicability
               Statement for Extensions to RSVP for LSP-Tunnels", RFC
               3210, December 2001.

   [RFC-3213]  Ash, J., Girish, M., Gray, E., Jamoussi, B. and G.
               Wright, "Applicability Statement for CR-LDP", RFC 3213,
               January 2002.

   [RFC-3270]  Le Faucheur, F., Wu, L., Davie, B., Davari, S., Vaahanen,
               P., Krishnan, R., Cheval, P. and J. Heinanen, "Multi-
               Protocol Label Switching (MPLS) Support of Differentiated
               Services", RFC 3270, April 2002.

   [RR94]      M.A. Rodrigues and K.G. Ramakrishnan, "Optimal Routing in
               Shortest Path Networks", ITS'94, Rio de Janeiro, Brazil.

   [SHAR]      Sharma, V., Crane, B., Owens, K., Huang, C., Hellstrand,
               F., Weil, J., Anderson, L., Jamoussi, B., Cain, B.,
               Civanlar, S. and A. Chui, "Framework for MPLS Based
               Recovery", Work in Progress.

   [SLDC98]    B. Suter, T. Lakshman, D. Stiliadis, and A. Choudhury,
               "Design Considerations for Supporting TCP with Per-flow
               Queueing", Proc. INFOCOM'98, p. 299-306, 1998.

   [SMIT]      Smit, H. and T. Li, "IS-IS extensions for Traffic
               Engineering", Work in Progress.

   [WANG]      Y. Wang, Z. Wang, L. Zhang, "Internet traffic engineering
               without full mesh overlaying", Proceedings of
               INFOCOM'2001, April 2001.

   [XIAO]      X. Xiao, A. Hannan, B. Bailey, L. Ni, "Traffic
               Engineering with MPLS in the Internet", IEEE Network
               magazine, Mar. 2000.

   [YARE95]    C. Yang and A. Reddy, "A Taxonomy for Congestion Control
               Algorithms in Packet Switching Networks", IEEE Network
               Magazine, p.  34-45, 1995.

13.0 Authors' Addresses

   Daniel O. Awduche
   Movaz Networks
   7926 Jones Branch Drive, Suite 615
   McLean, VA 22102

   Phone: 703-298-5291
   EMail: awduche@movaz.com

   Angela Chiu
   Celion Networks
   1 Sheila Dr., Suite 2
   Tinton Falls, NJ 07724

   Phone: 732-747-9987
   EMail: angela.chiu@celion.com

   Anwar Elwalid
   Lucent Technologies
   Murray Hill, NJ 07974

   Phone: 908 582-7589
   EMail: anwar@lucent.com

   Indra Widjaja
   Bell Labs, Lucent Technologies
   600 Mountain Avenue
   Murray Hill, NJ 07974

   Phone: 908 582-0435
   EMail: iwidjaja@research.bell-labs.com

   XiPeng Xiao
   Redback Networks
   300 Holger Way
   San Jose, CA 95134

   Phone: 408-750-5217
   EMail: xipeng@redback.com

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Acknowledgement

Funding for the RFC Editor function is currently provided by the
Internet Society.